PD-1 drugs approved: MRK’s Keytruda (pembrolizumab), BMY’s Opdivo (nivolumab), ROG VX’s Tecentriq (atezolizumab), PFE/MRK DE’s Bavencio (avelumab), AZN’s Imfinzi (durvalumab). I think I got all those right (off the dome).
MGNX? INNOVENT? Walvax?, MRK DE bispecific, etc.

So, my guess is BGNE’s valuation is mostly a function of zanubrutinib, their potentially best-in-class BTK inhibitor. It would still make it a very expensive drug company. Further, my cursory glance at their data vs ibrutinib reveals no significant difference, at least in WM. Will have to keep looking.

Papers I’ve Read
Regulation of the neuropathy-associated Pmp22 gene by a distal super-enhancer. Pantera, et al. Hum Mol Genet 2018.
CMT1A is a big disease!

Acetylcholine Receptor Stimulation for Cognitive Enhancement: Better the Devil You Know? Baxter & Crimins. Neuron 98, 2018.
Quick preview of Vijayraghavan’s paper (to appear in next blog) showing muscarinic 1 agonists don’t aid cognition, at least in this weird animal saccade model.

Clinical Trials
Single-Dose PK Study of Benapenem in Healthy Patients. Sihuan Pharmaceutical.
Sihuan stock has dropped a bunch in the last 12 months or so. I always thought it was a little overvalued. Interesting to see a seemingly new carbapenem, however. Too bad antibiotics are no longer a viable business. It is humorous to see ‘reporters’ opine about how we’re facing a superbug crisis, when the facts are very different.

Neoadjuvant study of pyrotinib in combination with trastuzumab in patients with HER2 positive breast cancer. Jiangsu Hengrui Medicine Co.
JH is the largest mainland China listed drug company (about $30B USD market cap). The financials are not in English. I am slowly learning Mandarin.

Study of the Safety and Efficacy of APR-246 in Combination with Azacitidine. Aprea Therapeutics AB.
This is why it pays to read random clinical trials all day. Aprea apparently developed a mutant p53 chaperone. The response rates are fairly good. I wonder if there are any papers or patents some friends are willing to mail to me on this mysterious new drug. p53 has been this important tumor suppressor for so long, but largely undruggable for somewhat obvious reasons. Given the revolution in tumor genotyping, it makes sense that restoring abberant p53 function (akin to the Vertex approach with misfolded CFTR) would be useful.

Treating paroxysmal noctural haemoglobinuria patients with rVA576. Akari Therapeutics.
This drug has been through a lot. I almost bought it 4 or 5 years ago as a competitor to Alexion’s Soliris. Recent studies have shown it appears to be not quite as effective as the real McCoy. Eculizumab is, of course, being replaced by an even better antibody. There are other anti-complement drugs out there. Still, at a $30m market cap or so, Akari is tantalizing (that does not mean attractive).

Virtual Reality for External Cephalic Version. Columbia University.
External Cephalic Version is when the baby is coming out upside down. Usually you have to C-section that, but you can try and flip the kid around. I guess the VR would help momma through that presumably traumatic process? Or train the doc?

Factor VIII Gene Therapy Study in Patients With Hemophilia A. Drug: BAY2599023 (DTX201). Bayer, Dimension Therapeutics.
Ultragenyx owns Dimension now. So many players in curing Hemophilia. Looks like BioMarin may be a year ahead of most.

Sorry I’ve been very busy lately! I was somewhat ill the last few days. I’ve been working hard on some math problems, some of which I may have solved. I’m reviewing lots of medical literature and data I’d rather not share, and I reviewed the appeal of my criminal case, which will be filed in short order.

Our building won the first series of our softball tournament, so I’m also pleased by that.


I am going to ask my friends to aggregate all of the glossary terms into a separate page, since some of you are interested in the multi-disciplinary requirements of being a pharmaceutical investor. Could be a good self-quiz.

CERC looks like a great stock and company. The people, investors, assets and strategy involved in the company are exceptional. They’re cutting deals at great prices–reminiscent of some of my early deals at Retrophin.

I still like GBT and old favorites like GILD ALXN REGN and the hemophilia stocks SGMO QURE ONCE BMRN ALNY RARE. PTCT has done so well but still has more room I think. The ACAD short is probably over. NKTR should eventually go to zero as their IL-2 drug is, well, IL-2. My favorite short is now BGNE.

Poor Pabrai, Carlisle and all of the similar folks in that self-deluded “circle”. I think there is a “value investing” community of small funds & moonlighting stay-at-home Buffett wannabees that think Graham & Dodd still works. Why doesn’t Buffett do it anymore? Why are all of the “value” funds being obliterated? The world has moved on from “buying low EV/EBITDA”. That stopped working like 30 years ago. You’re buying beta and patting yourself on the back. I hate to mock those beneath me, it feels like beating up on a patient with intellectual disability, but consider it a service to the hopefully able-minded. If your Sharpe ratio isn’t above 1, stop until you figure out why. If your drawdowns are enormous, stop and figure out why. If your beta is enormous, stop and figure out why. Investing isn’t easy. There’s no “magic formula” or “little book”. Point out someone who has gotten really rich doing this, and if there is some random moron who has, I can point out the fallacy and why they actually did well (accidental beta is usually the reason). Value companies, yes. Buy the cheap ones, yeah. Short the expensive ones, for sure. But that’s not simple. You can’t do that with “screening”. It’s enormously hard work that requires intense insight, preparation, training and exhaustive application. No shortcuts.

You might wonder what Wall Street books I actually like. One I enjoyed and read while at the MDC was “The Physics of Wall Street”. Another would be “Snowball” by Schroeder. I don’t recommend “Flash Boys”, which I felt was a rather misleading and incomplete look into high-frequency trading, or the two books I’ve panned here. I don’t ready many books on investing or business, but I certainly get these books unsolicited and read them when I have time. I read “Four”, which I wouldn’t recommend. Alibaba: The House that Jack Built was okay. Definitely didn’t help me to understand a fairly instructable guy. I got deliveries of “Principles”, “Shoe Dog”, “Barbarians at the Gate”, “Market Wizards” and a dozen more, but didn’t have time and left them behind at MDC.

Interview Questions – Part 2
Getting to know a personality is the trickiest part of the HR process. It’s relatively easy to measure aptitude, confidence, analytical approach, etc. It’s hard to know if someone is motivated, psychotic, greedy, loyal, etc. You want people that eat, sleep and breathe their field. In this case, people that love pharmaceuticals or investing (or both) so much, they’d do it for free. A good sign of that comes from the person’s history and why that got into the field. Tracing their life history helps. I am wary of people who have a very active social life, lots of interesting hobbies and other distractions. Work-life balance is great and necessary for well-adjusted behavior. However, I’d rather have the person obsessed with their field. A little unhealthy. The person who reads that last paper in AJHG at 11:30pm on a Friday is more likely to be useful to the company than anyone else.

With respect to our within-group analysis, any old investigational drug can have a meaningful reduction in symptoms from baseline, but only an investigational drug that can do that better than placebo is a real drug candidate 🙂

Paper’s I’ve Read
Forebrain-selective AMPA-receptor antagonism guided by TARP gamma-8 as an antiepileptic mechanism. Kato et al. Nature medicine 2016.
These Lilly scientists did an incredible job targeting a circuit/brain area-specific receptor by exploiting slight differences in auxiliary proteins the AMPA receptor uses. CERC now owns this compound. Wonder why LLY sold it…?

Mechanisms and clinical activity of an EGFR and HER2 exon 20-selective kinase inhibitor in non-small cell lung cancer. Robichaux et al. Nature Medicine 2018.
A tremendous end-to-end (“translational”) series of experiments starting with exon 20 mutation modeling , moving to cell lines and finally robust human responses. How it should be done. One worry is afatinib looks potent enough to compete with poziotinib. Poziotinib US rights are owned by Spectrum. The compound was created by Hanmi (I think), showing us sourcing molecules from the Asia region is always worth looking at.

Extending a systems model of the APP pathway: separation of beta- and gamma-secretase sequential cleavage steps of APP. van Maanen et al. JPET 2018.
JPET is usually a great journal but when it gets into systems biology and PK-PD modeling, I think there is more hand-waving and voodoo than real science. Take for instance, this paper. All the fancy differential equations in the world don’t explain the empirical phenomena accurately if we’re testing the wrong media and have a poor understanding of the PD. The “GSI” used here is around 1uM, not exactly potent, and we learned from the recent Shionogi paper I reviewed that a lot of GSIs aren’t really GSIs and beta-amyloid may be sequestered intracellularly. So here, the investigators (including Merck & Co researchers), took a brain port straight from the cisterna magna, but I’m not sure that is the right call either. So you have this fancy PK-PD model but it’s all “GIGO”, another important acronym 🙂

Enzalutamide in Men with Nonmetastatic, Castration-Resistant Prostate Cancer. Hussain et al. NEJM;38:2465-74.
The “PROSPER” study had predictably great results for Xtandi, HR=0.29(!). Revenue for Zytiga (abiraterone) is incredible. I have to dig up Astellas financials to see were Xtandi is, I think somewhat behind. Will be interesting to see how the new J&J drug from their Aragon deal (Erleada/apalutamide) does. But no mistaking that HRPC is getting more and more manageable, which is resulting in an even bigger patient pool. At some point in the future, more men over a certain age (perhaps 80) will have prostate cancer than not.

Progress in Nonmetastatic Prostate Cancer. Matthew R Smith. NEJM 2018;376;26:2531-2532.
There won’t be any way to test new drugs in this illness. Just takes too long. Maybe move to PSA as an endpoint?

Inhaled Corticosteroids and LABAs–Removal of the FDA’s Boxed Warning. Seymour et al. NEJM 2018;376;26:2461-2463.
FDA eats crow. The studies they asked for didn’t even answer the right question. I bet a lot of people actually suffered for this mistake. Having said that, you can never be too careful in their shoes.

Clinical Trials
Safety and Efficacy Study of Dual Specificity CD19 and CD22 CAR-T Cell Immunotherapy in Relapsed or Refractory Lymphoma. Nanjing Legend Biotech Co.
Ruh oh.

Investigating the Acute Effects of Blueberry (Poly)Phenols on Vascular Function and Cognition in Healthy Individuals.
I don’t even need to see the results.

Humor Therapy and Distress After Allogeneic Stem Cell Transplantation.

aliphatic – hydrocarbon without delocalized (pi) bonding. only sigma bonds. saturation doesn’t matter. contrast with aromatic. typical compound here would be cyclohexane, propane, etc.
anamneses – patient’s account of medical history
aromatic – hydrocarbon with delocalized (pi) bonding. benzene and its derivatives are aromatic.
binding pocket (aka orthosteric site, binding site, active site) – The typical location on a protein where a drug makes a binding (usually ionic) event. Keep in mind enzymes can have several active sites. Drugs that don’t bind at active sites are called allosteric binders.
diathesis – disposition to disease
kinase – enzyme which phosphorylates its substrate
steric hindrance –
Western Blot – lab technique used to detect proteins using antibodies and gel electrophoresis. Not very quantitative, more used for qualitative (yes/no) type questions.


Interview questions for an incoming pharma/biotech BD/M&A analyst follow. No one can do this job effectively by themselves, so hiring the right people is essential. The list isn’t exhaustive but reflective of my own interview style. Answers or reasoning for questions are at the bottom.

1. Describe the cell cycle in as much detail as you can.
2. If you were to receive $1 annually on 1/1/xxxx from a reliable party, what could you sell this income stream for?
3. Company A generates $10 million in stable, recuring income/cash flow from $100 million in revenue. Company B is the same as company A, except you are told that Company B has a $10 million annual party (still $10m profit on $100m in revs). What would you buy company A and company B for?
4. What is the most surprising clinical trial result you’ve seen?
5. What drug in clinical trials today do you believe will fail?
6. What disease state offers the largest business opportunity for a new medicine and what approach would you take?
7. Name 3 undervalued public biopharma companies.
8. Describe a large scale protein production process in as much detail as you can.
9. Describe the prototypical (perhaps stereotypical) physiochemical properties of a psychiatric medicine in as much detail as you can.
10. What element are you? Why?
11. What medicine do you most admire? Why?
12. Two companies, Pfizer and a small biotech company, are vying to bring a new class of medicines to the market. Pfizer is one year to two years ahead of the small biotech company. Hypothetically assume Pfizer has a change of heart unrelated to the programs’ prospects and you can acquire either program for $50 million. Assume the separate programs have an identical likelihood of technical/regulatory success. What questions do you need to ask to inform your choice?
13. In what circumstances has a method of use patent been upheld?
14. Give some examples of revenue size by country of a pharmaceutical. Be as detailed as possible (revenue in Germany, Japan, China, France, etc).
15. What type of return in achieved by: venture capital funds, internally derived R&D, acquisitions, healthcare private equity and healthcare hedge funds. Is there an optimal capital allocation process for a pharmaceutical investor?
16. What went wrong for Valeant?
17. A paper appears in Nature detailing what appears to be a tremendous advance in a therapeutic area by means of a preclinical experiment. The university team is willing to license the work to you for $5 million. What do you do to ensure your maximize of success?
18. A drug candidate has a 50% reduction in symptoms from baseline with a within-group p-value of 0.0001. In this placebo-controlled study the across-group comparison p-value is >0.05. What is your interpretation of this result?

Book Review: The Acquirer’s Multiple by Tobias Carlisle
One of you philistines sent me this, unsolicited. An appropriate subtitle would have been: Sophistries from a Confused “Value” Investor.

I have no idea who Tobias E. Carlisle is. Does anyone? Don’t write books about things you haven’t done. I’m not going to write a book called “How to Win the NBA Finals: Secrets of the Hook Shot”. It’s hard to write a book about investing if you haven’t done it and done it really well. What brings someone to the point where they feel they have to regurgitate the limited knowledge they’ve acquired in a field? Is it their tremendous writing skill? Carlisle provides zero evidence of creativity or aptitude in English language word selection and ordering. So, it must be that what he has to say is so important and learned that we should ignore his inability to articulate it!?

No. The actual content of the book is laughable. I was astonished at many points during reading that someone, even the author, thought this template of inanity was worthy of reproduction. The book begins by introducing a few concepts and platitudes which annoyingly recur. Carlisle’s writing strategy is to repeat his maddeningly ambiguous “point” so frequently and without variation, it borders on absurd. Mean reversion is the most powerful force in investing, the author would have us believe. I assume Mr. Carlisle is long Sears, Radio Shack, Toys R Us, Gap, American Eagle, Pacific Sun and is short Amazon and still waiting on that mean reversion. Me? I have a long list of biotech stocks that failed Phase 3 trials and went bankrupt, I’m long those, and short Gilead, Roche and Novartis as what goes up must come down. Gravity just doesn’t have the same sway Newton predicted in the strange universe of equities pricing.

Carlisle keeps talking about how one has to defy the “crowd” to be a successful investor. But what is the “crowd”? Or even the “market” for that matter? Carlisle doesn’t realize these are silly adages bereft of logic. “To beat the market you have to do something different from the market”. Really? So to outperform the S&P I have to not be long every single stock in a size-weighted approach? Tautologies abound for the forsaken person who has received this book as a twisted joke of a gift.

Carlisle insists mean reversion is the force that pushes up undervalued stocks. No. I define that force as “alpha” or “arbitrage” (it is also the size of the delta between market price and our derived price). In my framework, over time, alpha approaches 1. Mean reversion has nothing to do with it. For instance, a drug company worth $1 billion announces a breakthrough. The stock goes to $5 billion and stays there for 5 years. They plan another breakthrough, it seems like it will work, but the market doesn’t notice it. You go long. They announce the breakthrough and the stock goes to $15 billion market cap. The gap closed because of alpha realization, not mean reversion.

Another absurd tautology: Undervalued stocks tend to beat the market. A child could tell you that ONLY undervalued stocks beat the market. Of course, as we’ll painfully learn, Carlisle thinks that undervalued stocks are those with low earnings ratios. Yes, the key message of this book is to buy stocks with low P/E, EV/E, and finally, the eureka moment that rivals Einstein, EV/EBIT. Buy low. Sort a list of stocks and buy the low ones and you get rich. That’s what the book says.

Empiricism should never trump logic in investing. The greatest human folly of logic is ‘it happened before so it will happen again’. The amount of money lost, lives lost and destroyed productivity that groundless but intrinsically attractive repetition of prior processes to achieve future results has cost our species is immeasurable. Carlisle doesn’t provide any data or serious methods to allow the examination of his claims. He excludes a large number of stocks, and only US stocks for only short periods of time, where the market did extremely well. One obvious hidden bias to his approach is cyclicality. When the economy is doing well, and the US has done very well, and booms are longer than busts, cyclical stocks do better than the market because of the surprising economic resiliency. Recessions are shorter than investors thought, so stocks do better. Without shorting corresponding stocks, its hard to really know what alpha this system generates. We can see it generates a terrible drawdown and a Sharpe Ratio no better than the market. No serious quantitative investor would ever employ this “algorithm”.

It takes a lot of audacity to write a book that says “buying stocks that meet this secret criteria will make you rich!”. Okay what’s the criteria!? “Low earnings ratio!”. I wanted to throw “TAM” across the room when I realized the writer’s core message. Most of the book is similar to “The Dhando Investor” in that it parrots Buffett, but also includes genuflection to more recent investors like Icahn & Loeb. Like a child nervously glancing at his parents at a piano recital, Carlisle hopes that the conjuring the authority of Buffett will lend credence to his system. Coincidences in Buffett’s approach lend no credence to Carlisle’s system any more than my own obsession with Cherry Coke has made me a great investor. What the author doesn’t realize is that the investors he tries to demonstrate his system emulates have their best days behind them and new methods replace old. Prior world record holders would not qualify for today’s Olympics. We laugh at chess games from the early 1900s and know a moderately-ranked master would likely be the World Champion of 1912. Virtually any competitive sport or activity has the same dynamic: chess, poker, running, surgery, and definitely investing. You can’t look to the past. The people who we are to emulate and admire according to Carlisle were mavericks and innovators. You’re not being an innovator by copying what someone did in 1955, or even in 2000. To beat the market, maybe you have to do something new.

Amazingly, Carlisle advertises his stock screener (only 9.99!) in the book. Anytime someone promises you the fountain of youth, or in this case, the fountain of money, in a “little book” that does something that is very hard to do, but only is asking for your patronage somewhere else, run away. There is one page of marginal interest on overthinking that cannot excavate the reader from the intellectual cave this book builds. Nevertheless, I would recommend “TAM” to a small child (age 6 to 11) curious about the markets. It is simple, short and sets the reader up for more serious thinking later.

Papers I’ve Read
Combined Analysis of Asthma Safety Trials of Long-Acting Beta2-agonists. Busset et al. NEJM 2018;378:2497-2505.
I wonder how many publications gave the “all clear” signal after writing some scary article about LABAs. I really want to campaign that science writers actually get some (I know this is crazy) science experience. Notice the mITT HR=1.24? Only thing I found unusual here, whatever mITT definition that differed from ITT moved this from no trend HR=1.09, p=0.55 to trend HR=1.24, p=0.13. If it didn’t bother the FDA, it doesn’t bother me. Goodbye black box.

I might quit trolling. This wouldn’t be a permanent retirement as much as it would be a shift in focus. I intend on doing fewer in frequency but higher-impact public performance art style trolls (eg Wu-Tang). I have been heavily influenced by a loved one in this regard.

I have been busy reading proprietary research and, of all things, working on math. I am particularly interested in algebraic number theory–if anyone out there is a or knows a professor in this field, I would love to compare notes. martin@thotpatrol.com is the best place to contact me.

1. I don’t really care if an applicant understands the cell cycle (unless they got a PhD in cell biology and wrote papers on anaphase dynamics!) or can tell me about non-inferiority margins and esoteric statistics or anything else. I’m trying to determine if the person is self-confident, honest, humble, ashamed, self-conscious, etc. after being asked a technical question. The number of people who tell me they have statistical experience or chemistry experience only to swing and miss a softball technical question is large. If you can fluster someone with a softball, they’re probably not a good fit.
2, 3. See question 1. Answer for 2. is $10-$20, 3. $75m for Company A and $140m for Company B.
4. I have a lot of answers to this one. Perhaps the nusinersen results were the most eye-opening in recent memory.
5. Any beta-amyloid mab trial in mild-to-moderate patients.
6. Alzheimer’s disease is the easy answer. Parkinson’s is a great underdog. Autism would be an intriguing answer. polyQ disorders would get a gold star. Treatment-Resistant/Cognitive-Impairment in Schizophrenia would be an accurate answer. Neuropathic pain is not a bad choice.
7. Well, you can read my blog! I’d say GBT.
8 & 9 See 1.
10. Fluorine! Hungriest element! Personality is important. I’m curious how creative candidates are. I’ve asked people what superhero they most identify with.
11. Similar to #10, looking for creativity and values. A bit of a Rorschach.
12, 13 & 14. More general industry knowledge. On #12, first isn’t always best. 13. Rarely, Viagra is probably the biggest example. 14. Most have no idea the relative size of revenue by country–somewhat dependent on the type of medicine.
15. Testing the candidate’s understanding of capitalism. The point of any capitalist entity is to deploy capital and engineer a return on it. So, a drug company is in competition with a drug hedge, private equity or venture capital fund. How are those investors doing? What are they doing?
16. Overpaid for acquisitions as they scaled, NOT Philidor or price increases.
17. Replicate the experiment internally before forking over the big $.
18. No treatment effect.


Ovid’s data look flimsy.

Opdivo and Keytruda are approved in China. CStone and countless others are in pivotal trials. AstraZeneca has a long history in China and you can bet will register Imfinzi there. I’m not sure what Roche’s or Pfizer’s ambitions are, but they also do strong business in China and have globally registered PD-1s. So there are at least 6 PD-1 mabs I can name off the top of my head that are China-approved or likely to be that do not come from Beigene. But Beigene has a very large market capitalization. This will not persist. I have not seen something like this in a long time.

Lots of interesting companies to look at. Constellation, Summit, Fibrogen and so many more. Not enough hours in the day!

Is the world ready for biosimilar orphan drugs? Cerezyme and Myozyme aren’t tiny. I guess we have a few “me-toos” but they’re not cheaper.

Interesting article in JAMA my father sent me on body dysmorphic disorder and social media photo editing software as a trigger for this disorder. BDD is real: if you’ve ever seen someone with large amounts of plastic surgery, they likely suffer from BDD. But there are plenty of people who suffer quietly. Most people are probably unconsciously affected by societal progression of beauty standards. There’s a reason I’m attracted to Lindsay Pelas and Jen Selter–it’s mostly because I’m a man and they largely embody deeply inherited/evolutionary desires of man. So what if they understand that and have perfected it? We’ve reached the singularity of female desirability and the technology-enabled enhancement (both photographical and biological) of it. What’s next? I don’t know.

Always study the history of the industry you’re following. For biopharma, be familiar with companies like Cetus, Chiron, MedImmune, Centocor, Immunex, HGS, Genentech, Genzyme, Idec, Millennium, ICOS, Vicuron, Athena, Genta, Sugen, Warner-Lambert, Pharmacia, Syntex, Abgenix, Triangle, CV Therapeutics, Pharmion, Sandoz, Ciba-Geigy, RPR, ICI, Aventis, Parke-Davis, Scios, COR, Imclone, Medarex, Atherogenics, Telik, Tularik, Intermune, Elan, Northfield, Vion, GenVec, Cell Genesys, Pharmasset, Idenix, ViroPharma, NPS, Myogen, MGI, OSI, Synta, Trimeris, TKT, Aviron, GI, Tanox, and so many more. There is some wisdom in history. You have to mine for it, distill it.

Papers I’ve Read
Functional gamma-secretase inhibitors reduce beta-amyloid peptide levels in brain. Dovey et al. J Neurochem 2001.
I guess this Elan/Lilly paper started the whole semagacestat/gamma-secretase mess. They go up to 200mg/kg (!!!) dosing in these experiments with their putative GS inhibitor DPAT. Its very hard to trust any of the data given what we know now about APP processing and intracellular retention. Still, you can see the errors in judgment with the high-powered lens of hindsight. It’s also funny to see what passed for a screen in 2001.

The gamma-secretase inhibitor N-[N-(3,5-Difluorophenacetyl)-L-alanyl]-S-phenylglycine t-butyl ester Reduces AB Levels in Vivo in Plasma and Cerebrospinal Fluid in Young (Plaque-Free) and Aged (Plaque-Bearing) Tg2576 Mice. Lanz et al. JPET 2003, 305:864-871.
Pharmacia workers “replicate” Dovey. Same issues. I think everyone was okay with the 100-200mg/kg dose given low brain partitioning and a cell-based assay affinity of ~100nM. It’s really hard to tell what these ELISAs are picking up and what species are relevant for aggregation.

I’ve received around 500 books by mail since I entered the prison system. There is a Twilight Zone episode, “Time Enough At Last” (I think that’s what it is called!), that summarizes my feelings on having a lot of time to read. It’s a joy, but I don’t exactly have the shelf space. I probably have around 50 books here at Fort Dix. This is still far too many. So, please don’t send me any books without my knowledge! They will probably end up donated or thrown away. Also, if you mail me, it must be in a plain white envelope with plain white paper. No stickers, glitter, or contents other than paper. No stamps.

Sarah Jeong joining the New York Times is a disgrace. This woman is not a satirist, she has truly backward and painful racial beliefs. We should ask her some simple questions to clear up her “satire”. If you did the same to me, it would look like this:

Q. What do you really think of Hillary Clinton?
A. I think she is an untrustworthy parasite of politics. She should not hold office and represents what is wrong with the American political system.

Q. But why?
A. Just look at how much money her family has made through “speeches”. That’s basic influence peddling. I don’t expect Bill Clinton to become a store clerk after being President, but to become a high-paid lobbyist is a bit disgusting. They’re certainly allowed to be capitalists, but the irony of HRC railing against the rich is not unnoticed.

Q. Do you wish harm on the Clintons?
A. No. I admire all Presidents, once elected. As someone who has achieved a lot, the Presidency is the ultimate achievement and I respect the winner of such an arduous contest. I haven’t yet seen a President so contemptuous to break this ingrained respect. I also begin my analysis of a candidate with a “clean slate”, once elected. I would have done the same for Hillary.

If you did that with Sarah Jeong I think she’d have a hard time disavowing some fairly extreme views. I’d like to see the demographics of the New York Times staff and its readership. I wonder if “white people” are high on that list. I also want to remind Ms. Jeong that Asian Americans are now the highest earners in the United States. There are a lot of poor, uneducated and very, very non-privileged white people. Racism is painful and shameful, but society must grow and move on. Never forget, but learn and grow. What is Jeong adding to the conversation?

strabismus – crossed eyes


Always remember that investing is simply price calculations. Your job is to calculate accurate prices for a bevy of assets. When the prices you’ve calculated are sufficiently far from market prices, you take action. There is no “good stock” or “bad stock” or “good company”. There’s just delta from your price and their price. Read this over and over again if you have to and never forget it. Your job is to calculate the price of things and then buy those things for the best price you can. Your calculations should model the real world as thoroughly as possible and be conservative in nature.

Neurocrine is selling a lot of drug. Sometimes you’re wrong! Good for them.

It’s the end of an era for Johnson & Johnson as Stelara takes over Remicade as their best-selling drug. What an achievement, and mostly on psoriasis? Kind of incredible how patients will be diagnosed the more a treatment is effective. Build it and they will come!?

I’m going to start including “Patents I’ve Read”, as a very important source of knowledge that I try and keep up with.

Papers I’ve Read
Computation through Cortical Dynamics. Driscoll et al. Neuron 2018.
This… this is a paper on computer science? 10-dimensional data can’t be visualized? Hold my beer.

Hearing out Ultrasound Neuromodulation. Airan and Pauly. Neuron 2018.
Funky ideas debunked. Ultrasound evokes an auditory response even at inaudible frequencies. Probably useless for neuromodulation.

Noninvasive blood tests for fetal development predict gestational age and preterm delivery. Ngo, Quake, et al. Science 2018, 360, 1133-1136.
Dr. Quake out with another banger. Drake should take notes. The cell-free fetal RNA test looks at the mother’s blood to determine delivery date. It’s as effective as ultrasound, which was a little disappointing, but my guess is it will be optimized. Pretty amazing!

Subclinical Hyperthyroidism. Biondi & Cooper. NEJM 2018.
Just in case you needed to know about a disease with no symptoms or sequelae.

Reboxetine in therapy-resistant enuresis – a randomized placebo-controlled study. Lundmark et al. J Pediatric Urology 2016.
If you’re old enough to remember Pfizer developing a reboxetine isomer, good for you. The problem with bringing reboxetine to the US is you have atomoxetine which is functionally similar (and generic). So, you could spend a lot of money “repurposing” reboxetine for ADHD, enuresis, NOH or god knows what else, and probably do just fine, but I don’t do just fine, do I?

Chronic delta9-THC in rhesus monkeys: effects on cognitive performance and dopamine D2/D3 receptor availability. John et al. JPET 2017.
I’m all for getting monkeys high and seeing what happens. Apparently you develop a tolerance to some cognitive impairment and whatever else goes away after two weeks of abstinence. Legalize away!

Long has paled that sunny sky;
Echoes fade and memories die,
Autumn frosts have slain July.

You can imagine how surprised I was to receive a book from “Ringo” today. Ringo is a member of the canine species, and said member unfortunately lacks a uniform color. Nevertheless, despite his polychromicity and limited intellect, he successfully mailed me “Quantum Physics of Atoms, Molecules, Solids, Nuclei and Particles by Eisberg and Resnick”. This is a subject I know little of and hope to know even less. It will fit snugly on a planck under my bed until Ringo learns how to respect members of the feline species. Jokes aside, thanks you Ringo. May you outlive your namesake.

goiter – n – enlarged thyroid


Well, Yescarta is doing quite well, actually. $68m last quarter as per Gilead’s most recent quarterly earnings. That’s not awful! This is one-time treatment, however. So unlike most drugs, these patients aren’t paying a subscription fee. For Gilead that kind of reminds me of hepatitis C, but of course, unlike HCV, cancer patients don’t come from a “pool”, they simply arrive every year. It’s far too early to tell but generally a performance like this would suggest a $1 billion medicine, at least. Makes KITE a decent deal. However, as in all things, you can never know for sure. Next quarter could be down! The drug may plateau at $500 million or go on to $2 billion+ performance. No idea.

Surprised how well ABBV is holding up in Hep C.

It is still fascinating to me that drug journalists not only are unfamiliar with statistics, but they also appear to be rooting for drug companies to do poorly. The hatred towards AbbVie for not having biosimilars in the US is particularly funny. Are these writers taking Humira for rheumatoid arthritis? Do they think that biosimilars to adalimumab, which represents ~2% of US drug spend will save what they perceive is a healthcare crisis? Have they looked at AbbVie’s patents and have pointed out the prior art that renders them meaningless despite the respect shown by the biosimilar companies? Emotion trumps inference for the cognitively challenged.

Papers I’ve Read
Semagacestat Is a Pseudo-Inhibitor of gamma-secretase. Tagami et al. Cell Reports 2017:21, 259-273.
Tagami and Shionogi workers go on an interesting journey to learn more about gamma secretase. They draw very speculative conclusions but have a foundation: semagacestat INCREASES beta-amyloid intracellularly. So, if you’ve been playing along from last week (and you should), we have to solve a mystery. One solution is a simple law of conservation. If you have a pre-peptide (endothelin, angiotensin are good examples) and it has to be “processed” (cleaved) to create its final form, and you inhibit the enzymes that do this, you still have the pre-peptide (sometimes called a pro-peptide, or even a pre-propeptide.) If that entity aggregates, you’re in trouble. Peptides are eventually proteolytically degraded but if they are aggregation-prone, you’re out of luck. The writers assume semagacestat is inhibiting some other functional part of the GS complex, the part they speculate trafficks AB out of the cell. More work is needed, but it neatly explains all the results seen so far. This is a great lesson in preclinical experimentation: make sure you know what you’re measuring. AB in the “soluble fraction” (extracellular) may drop but if its being retained, you haven’t solved the problem.

Primary Prevention of Cardiovascular Disease with a Mediterranean Diet. Estruch et al. NEJM 2013.
As we close the semagacestat puzzle, here is a new one for young, would-be drug hunters. What do you see in this publication that is strange? Are the conclusions reasonable? Can we reject the null hypothesis? Why not? Answers in the next blog. Guess away in the comments.

Phase 3 Trial of Ibrutinib plus Rituximab in Waldenstrom’s Macroglobulinemia. Dimopoulos et al. NEJM 2018.
The “iNNOVATE” trial demonstrated a death-defying HR=0.20. WM is a weird little disease, often an afterthought given its relatively indolent nature compared to its cousins. Still seems like there could be an opportunity here for another agent.

Dupilumab Efficacy and Safety in Moderate-to-Severe Uncontrolled Asthma. Castro et al. NEJM 2018.
Efficacy and Safety of Dupilumab in Glucocorticoid-Dependent Severe Asthma. Rabe et al. NEJM 2018.
New Biologics for Asthma. Drazen & Harrington. NEJM 2018.
Great data. Asthma is a bigger disease state than folks realize. Very much looking forward to the Dupixent Q2 number.

The last post about intelligence requirements for STEM vs. the humanities was triggering. But, it was a trap! There has been enormous data generated recently that correlate intellect with educational achievement and even SAT performance (high R^2!). I must admit I’m probably going a bit too far when I say learning quantum physics is “harder” (requires more cognitive ability to perform adequately) than gender studies. One can be a master of each discipline. Was Einstein more of a genius than Shakespeare? No, definitely not. Was Shrodinger no less of a luminary than Duca? In all seriousness, I think a well-rounded education is important. I don’t write frequently anymore, but once-upon-a-time I thought I’d do it for a living. My problem with science business (pharmaceuticals, for instance) writers is they don’t know science or business. There are very few people who know both fields, and you can bet they’re not writing about it. Before you bicker about some prevailing inferiority complex, consider the above an advertisement: I’m doing it!

antibody – n – An immune system protein, “Y”-like in shape, composed of Fc and Fv regions. Binds to, and generally eliminates, a target molecule called an antigen, usually another large molecule/protein. Originally manufactured in mice (murine antibodies).
chimeric antibodies – n – Obsolete now, but antibodies created with a human Fc region and mouse Fv region.
complementarity-determining region (CDR) – region of an antibody that defines its binding to its target
consanguinity – adj – Related parents (inbreeding). Very common in rare genetic diseases. A restricted gene pool tends to result in autosomal recessive disease — the Amish, certain Jewish sects and other populations that simply don’t see much migration have a larger share of rare diseases.
epitope – n – exact binding site of antibody’s antigen.
eosinophils – n – a type of white blood cell that mediates an allergic/asthmatic response.
Fc region – n – “Framework constant” region of an antibody. The bottom part of the Y.
fully human antibody – n – generally created in transgenic mice where the mice are genetically modified to only create antibodies from human genes.
Fv region – n – “Framework variable” region of an antibody. The arms of the Y.
Humanized antibody – n – a chimeric antibody with a human CDR framework (much of which is constant).
intent-to-treat – n – for statistical purposes, the entire enrolled trial population, usually that was randomized and received at least one treatment dose. As opposed to per-protocol population, the pool of patients that completed the trial correctly. Test statistics are almost always conducted on the ITT population with missing data interpretation defined prospectively.
monoclonal antibody – n – See antibody. The monoclonal adjective distinguishes from polyclonal, in that monoclonals come from one source and have one epitope.
type 2 inflammatory response / immune response (Th2) – n – Elevated levels of eosinophils, IgE, IL-4, IL-5, IL-9, IL-13 and other immune markers that distinguish the response from Th1.


Biopharma & Investing
Alexion is kicking butt. Being this good is almost boring.

Gilead, both Johns are stepping down. Running a big pharma and being that good is boring too, I guess.

Keytruda approved in China. Big problem for Beigene.

BAN2401 is not a viable drug. It does not work. No way, no how. I think people who write about biotech for a living should write less quickly (and less from a company script) and read some textbooks on statistics, medicine and pharmacology. Friends email me news here and I was aghast to see nearly every biotech ‘observer’ pathetically record that BANB2401 produced a promising result. “Stat” (whatever that is), CNBC (predictable), Endpoints (this is that weird guy’s blog), etc. All the usual suspects just don’t know how to read clinical data. Why even try to chronicle the history of an industry if you just don’t get it? Maybe wait until the dust settles before writing an embarassing headline. It is really emblematic of an epidemic: media companies don’t have big budgets, so they hire whoever they can to write whatever they want on a field they don’t comprehend. I saw some financial journalists completely fail to comprehend amortization recently. A silent smile is all I can produce. So, I understand predicting the future is too tough for biotech writers, but at least chronicle the past correctly.

Anyway, the stock market promptly reacted to the BANB2401 data for the failure that it was. Antibodies don’t enter the brain, let alone the cortical areas, the parenchyma, etc. It’s fucking physics. F=MA? Tight junctions? Next, we saw what happens when a-beta antibodies are dosed in AD: bapi, sola, etc. Finally, THIS data is a piece of work. Don’t trust any p>0.01. That is the same as p>0.05. For Christ’s sake, don’t trust data at p>0.01. Drugs don’t work by chance, ever. At least drugs I care about. Next, the idea that one drug dose worked and one didn’t is humorous. Unless you have a clear explanation as to why one dose wouldn’t work and one would, you have to group and average the cohorts. The company wouldn’t waste precious power and resources if they thought there would be no activity in the dose cohort. Most antibodies stick around. It’s plausible that more frequent dosing would do the trick, but unlikely. Same thing with timing of therapeutic effect: the separation that occurs at 18 months has no trace at 12 months. Is there a plausible reason for that? Sure but I’d be more convinced if it persisted at 24 months. Very, very few drugs have a 12 month delayed therapeutic onset. FInally, this isn’t a clinically meaningful result (hence the p=0.016 or whatever it was). ADAS-COG is a 70 point scale. A 2 point improvement is exactly what these antibodies were invented to NOT produce. I’ve wasted enough transistor state changes writing this. I’m sorry, electrons.

Book Review – How Not to Be Wrong: The Power of Mathematical Thinking – Jordan Ellenberg
It’s hard for me to review a book like HNTBW. One lens to look at it through is, “could I have done better”? I’ll go through areas I think were lacking, but this is a paean to math that deserves your attention. Of course, One of Bill Gates’s “10 Favorite Books”, which I’m sure is a subset of a larger list of his favored reads, which is apparently, everything he reads.
The title of this book could not have been written by its author. It is largely meaningless. The title should have been: “My random thoughts on Math and Statistics which will hopefully get you interested in Math”. There is no theme that I could discern other than the author’s obsession with math history. So Ellenberg’s structural organization is very poor. He meanders from topic to topic, staying far too long on some (statistics), ignoring others completely. On the plus side, he is imaginative with references to F Scott Fitzgerald, the erstwhile mathematician Wallace (David Foster!) and various other compelling orthogonals. His actual writing style is excellent. Clearly a keen mind, he restrains himself from overpowering the reader with the standard philosophical/mathematical overwrought vocabulary. “He’s just an average joe math professor!” is the feeling you get and it keeps you engaged.
Ellenberg tries to do a good deed. His message is that this book will somehow help you think more structurally. It won’t do so, directly. There are very few (maybe two?) proofs in the book and other than a brief explanation of reductio ad absurdum, very few logical techniques are actually employed. Despite that, Ellenberg tackles hundreds of problems with a sneaky mathematical armamentarium. I fear his secret spies could have been more direct: on battalion, a little more actual math wouldn’t have scared the reader and empowered the work. Some of HNTBW feels like a parlor trick, with the reader forced to trust Ellenberg that “there’s math in here, don’t worry! I’m not going to show it to you, but it’s there!”.
Understandably HNTBW has a strong focus on statistics but here Ellenberg makes a very poor showing. In the classic example of multiplicity errors gone haywire, Ellenberg introduces the GWAS experiments that yours truly reviews on a daily basis but doesn’t describe p-value correction. This and other glaring omissions, like any discussion of why people insist on making post-hoc observations that fail to repeat themselves, could have served readers well.
The second half of the book is a more poetic journey through math history. While he is no Newman and this is no anthology, Ellenberg’s near lyricism is enchanting and awe-inspiring. The last chapter in the book is a monument to humility, creativity and achievement in maths. Still, HNTBW is not Godel-Escher-Bach, nor does it try to be. Ellenberg just teases us with math, often namedropping greats and taking us on a tour meant to enthrall us and learn more. A much-needed manual on how to actually think in a structurally correct way was a titular trick I’m happy I fell for. I highly recommend this book. 9/10.

Glossary – Dedicated to various journalists at Bloomberg, CNBC, Stat, etc. who I wouldn’t hire to change my cat litter because they apparently are unaware of the following:
a priori – generally used as a synonym for “pre-specified” in statistics.
alpha – the likelihood of making a type I error, or rejecting the null hypothesis when it is true
beta – the likelihood of making a type II error, or incorrectly concluding the null hypothesis is correct
clinical significance – as opposed to statistical significance, the degree to which a medicine is clinically relevant to a patient. 2 points on a 70 point scale, for instance, is not clinically relevant.
co-primary endpoint – if you split alpha a priori, you can examine two endpoints at once. however, both endpoints must be met with the reduced alpha to infer the rejection of ANY null hypothesis.
deductive reasoning – using the rules of logic to form inferences with certain conclusions.
Fisher, Sir Ronald – British statistician who was the father of statistics. Probably the first person you could call a statistician.
Fisher’s Exact Test – A personal favorite, a categorical statistical test for contingency tables.
Gauss, Carl Friedrich – Mathematical deity who the normal distribution is named after
inductive reasoning – find patterns in empirical data. any inference where the premise is giving us some evidence of truth, resulting in a probabilistic inference
inference – something many, many liberal arts majors are incapable of
mechanistic plausibility – The plausibility of an investigational drug’s mechanism of action. Similar drugs having failed to elicit a beneficial response in a similar patient population would impinge negatively on plausibility.
null hypothesis – the hypothesis we seek to invalidate with an experiment, a reductio ad absurdum technique
Pearson, Karl – another father of statistics, see Pearson’s chi-squared test.
p-value – the quantification of statistical significance, where the p-value must be less than alpha.
pre-specified endpoint – Typically, a between-group comparison using a statistical method that is articulated in the SAP prior to trial initiation.
primary endpoint – The ONE a priori statistical test hypothesized in the SAP. A clinical trial can only interrogate ONE hypothesis so as to avoid unduly respecting post hoc observations. IF the primary endpoint is met with statistical significance, a secondary endpoint may be evaluated as per the SAP with the same alpha level as the primary endpoint (no alpha is considered spent). Dose-ranging studies make pre-specified endpoints extremely hard to meet given the limited power of making each dose a co-primary endpoint. One may group all or some doses and retain full alpha, but one may not assign full alpha (0.05) for all doses. If 5 doses are being interrogated, the alpha must be SPLIT between these doses (roughly 0.01 each).
post hoc analysis – An after-the-fact analysis of data which is hypothesis-generating ONLY. Typically used by companies and characters of ill repute to bolster clinical trials which have failed to reach statistical significance. “Shooting an arrow and painting the bullseye after”.
power: 1 – beta
probability distribution: a description of probability of all possible outcomes in an experiment
statistical analysis plan (SAP) – the statistical protocol for a clinical trial
statistical significance – when p < alpha, the probability that the results obtained if the null hypothesis is true, were due to chance
type I error: rejecting a true null-hypothesis
type II error: failure to reject a false null hypothesis

Spend more time reading books and less time giving out an unearned opinion. I doubt many “communications” majors (or most other liberal arts majors) are intelligent enough (yes, I am going there) to have done well in mathematics and statistics. As Dalio says, ask yourself if you’ve earned the right to have an opinion. You should not opine on biopharmaceuticals unless the above is facile and simple to you. Statistics is the lens with which we see the modern data-driven world. Go back to school and actually learn something, if you have to. The above are trivially basic–we don’t go into Bayes vs frequentist, ANOVA, actual math of a statistical test, stratification methods, parameterization, multiplicity correction techniques, LOCF/BOCF and missing data and other still simple topics.


Biopharma & Investing

I like Global Blood Therapies’ (GBT) drug. I’m still not through with my work but I suspect this is a real disease-modifying drug that treats the underlying cause of sickle cell anemia. A real breakthrough. This company may become as large as an Alexion or Onyx (pre-takeover) in due time.

CAR-T looks like a commercial dud. Sorry, Celgene and Gilead. Those billions are unlikely to come back. Who knows, though. Antibodies had slow uptake at first. What I’ve heard from various sources is institutions don’t want to do CAR-T. The side effects are tough and the reimbursement is difficult. This is good for companies like Morphosys and Seattle Genetics who are using traditional antibodies for CAR-T targets and some are seeing good results. Bad news for the 200 private CAR-Ts, ADAP, CLLS and everyone else who wants to be JUNO and KITE.

The flu market is heating up with new drugs from Roche, Shionogi and Vertex and some promise of a universal vaccine.

Idorsia is chugging along with their rHTN (resistant hypertension) ERA (endothelin receptor antagonist). Guess who also bought an ERA way back when 😉

Starting to watch the vaccine space very closely. One of the few areas of pharmaceuticals that is truly cost-effective, hard to replicate/genericize, etc. Every new vaccine company seems to get acquired (IDBE, CRXL for you old timers).

Papers I’ve Read
I’ve been reading some proprietary materials, so excuse the lack of commentary.

GBT440 increases haemoglobin oxygen affinity, reduces sickling and prolongs RBC half-life in a murine model of sickle cell disease. Oksenberg et al. Br J Haematology 2016.
Tremendous work from the GBT team here. This panel of preclinical data is comprehensive. Almost every question I would have asked is asked and answered here. The murine transgenic model was a bit of a flop, which was interesting. Nevertheless, GBT440 certainly works as advertised, increasing Hb-O2 affinity, thereby raising the question of whether these HbS-GBT440 complexes are TOO oxygen-hungry and will never release this oxygen to tissues. It would still (or should still) stop polymerization of the aggregation-prone HbS species. One question I would have answered is trying to determine binding kinetics here, especially Koff. Km wouldn’t hurt, we see some EC50s in the micro molar range. The engineering of a compound devoid of plasma binding is somewhat surprising. If I had to decide on buying this whole company, I’d probably run that assay independently to be really sure as it is not often compounds have close to zero albumin affinity.

Clinical activity and molecular correlates of response to atezolizumab alone or in combination with bevacizumab versus sunitinib in renal cell carcinoma. McDermott et al. Nature Medicine 2018.
The IMmotion150 Phase 2 results. Nothing exciting here. Gene expression-guided treatment is a pretty neat concept and shows were Sutent actually does rather well.

New Developments in Anti-Sickling Agents: Can Drugs Directly Prevent the Polymerization of Sickle Haemoglobin in Vivo? Oder, et al. Br J Haematol 2016.
Decent review. Somewhat stunning that there are 20T (trillion!) red blood cells, which are most of your cells (!!!). Each RBC has 250 million (!) hemoglobin proteins. so that is … 2*10^13 X 2.5*10^8 = 5.0*10^21. You need 20% of that hemoglobin ‘fixed’ according to various in vitro studies, so 1.0*10^21. The MW of GBT440 is 337, so the weight of the drug you need is 3.37*10^23. Avogadro’s # is 6.022*10^23. So you need 500mg of GBT440, but the bioavailability of the drug is something like 50%, so you need 1g/day. That’s roughly what they dosed in Phase 3. Incredible!

I received a rather ineluctable haircut after “looking like Harry Potter” (at least to various other convicts) for far too long. One barber agreed to “give me the Brad Pitt” after discussing various style options. Consequently, I have very little hair left. No longer hirsute, life goes on! Just like the memes, barbers here also insist on reciting “say no more, fam” prior to destroying your appearance.

Why does Bill Gates review EVERY trash book and think they’re good? Poor guy. Bridge & reading psychosocial commentary is one helluva retirement. At least his healthcare stuff seems well done. I’ll probably learn how to play bridge soon.

hemolysis (medicine, basic concept) – destruction of a red blood cell (RBC) that lyses the cell membrane and releases its contents
hemolytic anemia (medicine, basic concept) – anemia due to hemolysis
hematocrit (medicine, basic concept) – RBCs as a % of blood
aromatic (chemistry, basic concept) – adj – a compound with the presence of cyclic sigma bonds and non-localized pi bond
pi bond (chemistry, elementary concept) – delocalized bond present in a double bond (in addition to a sigma bond)
sigma bond (chemistry, elementary concept) – overlapping bond present in a single bond
aldehyde (chemistry, basic concept) – a functional group featuring a C=O bond with a R-C and H-C bond.
thiol (chemistry, basic concept) – a functional group consisting of R-S-H


Biopharma & Investing
–I left off musing about the inability for public equities to achieve a meaningful risk-adjusted positive return. This is an unorthodox and uncomfortable opinion I have tremendous conviction in. The impact of some of my opinion is derived from explaining the post hoc ergo propter hoc fallacy: folks who disagree with me point to historical returns instead of the underlying structure for what to expect from the future. History is not a guide for the future here, even 100 years of history. The US will never be in the same situation it was then, ever again (scale, globalism). Or there is a framing error: they are looking at US equities only, forgetting there are some failed states that want their stock markets back. I’m sure the Soviets and Japanese thought THEIR stock markets would always go up, too. Aren’t we all lucky to have been born here? Boris Buffetski and Waryu Buffetashi are missing in action. I’ll have more to say, not only on why historical returns for global equities are not that impressive on a real- and tax-adjusted basis, but also why structural flaws will limit future equity returns to very close to zero, if at all positive.

–Still working on the time-consuming Merck analysis. I’ve figured out the classification of all their drugs over the years. However, the vaccines are tricky given some of them have been refreshed for 50+ years! We’ll exclude the vaccine business for our purposes and adjust the R&D a bit. Still, huge hits like Fosamax, Singulair, Januvia and Zocor promise that Merck’s been far more productive than Pfizer. We’ll see what the final calculations say soon.

–Wealth can’t be understood without age-adjusting. Anyone who has read ‘Snowball’ or spent a lot of time thinking about compounding understands this. Getting a good head start is nice, but keeping pace is difficult. I’m going to make a chart of wealth on an age-adjusted and inflation-adjusted basis and run IRR calculations comparing individual wealth as you would corporate. Here’s the work on Buffett:

From 1958 to today, Buffett compounded his personal wealth by about 21.5%, from $1 million to $82 billion. I will try to undo some of his donations and see how he would have done by keeping all his BRK stock. I’m not sure what impact that’s had on his wealth.

At 30, Buffett’s $1 million of wealth is $8.5m in today’s money.
At 35 (my age), Buffett’s then $7 million of wealth would be $56m in today’s money. (So far so good for me!). From this age, Buffett compounded at 19.33%. That’s every year, for the next 53 years. Astounding!

At 43 (year is 1974), gaining steaming, Buffett’s $34m is worth $193m in today’s money. He compounds from 19% from here.

At 52, he’s worth $376 million, in today’s terms, $951 million. A billionaire. From here, he returns 16% per annum.

What’s amazing about WEB is we celebrate billionaires so much in today’s culture (except for CNBC, because they’re nazi socialist/communists), and he was a little late to the party. It shows you that wealth is about longevity and having the right mental framework for long-term success. Buffett whizzed past a lot of early birds with his consistency.

–Finally, a repeated thank you to the management team at Vyera who is delivering all this success for me. Would be nothing without you! Stunning R&D productivity with 4 INDs likely (3 already in the bag!) in just 3 years. May you keep compounding 🙂

Book Review – A Brief History of Time – Stephen Hawking

Dr. Hawking recently passed away and so perhaps he has taken a throne next to Einstein, St. Augustine, Descartes, Pascal and others in a room God marks as “Nice Tries”. Explaining the universe is a tricky avocation. Having ALS at the same time would make one’s job harder. Nevertheless, Hawking made profound advances in theoretical physics and cosmology which he has been duly lauded for. Many pop science writers are unpublished hacks, but Hawking had the scientific chops to straddle both worlds. While his disability made him a celebrity, and one wonders if he would have been as popular without it, or if some researchers secretly resented him for it, we won’t know and shouldn’t care.
About the book!? Right! Well, “A Brief History” is one of the most printed books of all time. It’s that bestseller that everyone has on their bookshelf and no one has read cover to cover. As a preteen/early teen I was a particle physics enthusiast, obsessing over subatomic taxonomy and I STILL didn’t read ABHOT, partially because I felt Hawking was TOO celebrated and partially because of its pop orientation. However, I admit for the early part of this period, I was awed and inspired by this computer-voiced crippled man who could still level you with his mind. And in ABHOT, Hawking does just that.
ABHOT is very far from a textbook, and it is too simplistic and even patronizing in parts (Hawking refers to Kant’s seminal Critique of Pure Reason as “obscure”). However, in general, ABHOT is mostly too difficult to fully understand and appreciate. I challenge the lay person to keep attention during Chapter 8, for instance. “The Origin and Fate of the Universe” is an abstract mess that is hard to follow unless you have an undying curiosity about this field. If this is your first time encountering spin states, the cosmological constant, or even simple quantum mechanics, you will be lost trying to follow this work.
If understanding the universe is a tricky business, then perhaps explaining the universe is even more difficult. I don’t fault Hawking for sometimes deliberately leaving out crucial mathematical details. He goes on to say “well, I proved this” and “this theory requires that” but leaves the reader without evidence of his line of thinking, only his grand authority. I won’t cavil about the published refusing the words billion and trillion, instead relying on “6 million million million”, as if this is an easier concept to understand than scientific notation. Hawking annoyingly explains in parentheses how many zeroes the author is indicating. The book is too short to be useful–at less than 200 pages of the main text, some necessary core concepts are completely eliminated. We’re left with lots of questions about the nature of time, and perhaps that is the point. Hawking drills in over and over again that time is not linear in the sense that we understand it. It likely has no beginning, no end and no absolute measurement. He explains relativity and spacetime reasonably well but he doesn’t evoke the wonder you might expect in such a numinous subject. For the more mundane concepts, the reader will be bored. Do you really care what happened in the femtoseconds after the Big Bang? Hawking forgets his audience with excursions that can sometimes be painful.
Concepts like black holes and radiation they emit are again, far from terrestrial, even in his attempt to ground the subject matter. Advanced readers are simultaneously puzzled and frustrated by a lack of detail and all-too-frequent hand-waving and progression of a concept. A more detailed work would be even drier, and perhaps risk only 0.5% of purchasers reading the book than the current 1.0%. Still, if you’ve have had any exposure to physics, ABHOT is a relatively fun breeze which should rekindle some interest in wonderous entities like gravitational waves and particle colliders. I fondly recall a childhood where I’d exhaust my schoolmate Franky’s patience with latest developments at CERN–to what end are all of these atom smashers annihilating the unseen?
This is where ABHOT fails to become a transcendant work. For all the science, Hawking barely scrapes the philosophical surface. He rhapsodies briefly on the anthropic principle, but largely evades the important question and reason anyone bought this book. Is there a God? Do you see Him in those atom smashers and huge telescopes? A signature perhaps? Anything you can tell us about why we’re here, where we came from and where we’re going? Hawking flirts with the concept of a diety but only when its comfortable and it feels perfunctory and obligatory. Perhaps a new version would have some important updates from the author.

Papers I Read
Proximity to Parental Symptom Onset and Amyloid-Beta Burden in Sporadic Alzheimer Disease. Villeneuve, et al. JAMA Neurol 2018.
This is a very sorry paper. The main finding is r^2=0.08, p=0.04. I don’t see how journals publish stuff like this. Like, I get that you wasted your government or whoever’s grant money and need to show SOMETHING. Write a nice “we’re sorry” card. Don’t publish. Or just say you found no correlation and publish in some crap journal. Shame!

FBXW7 regulates DISC1 stability via the ubiquitin-proteasome system. Yalla, et al. Mol Psych 2018,23:1278-1286.
This Pfizer (and academic collaborator) paper shows strong, capable science. DISC1 is an important protein and it is degraded by a specific E3 ligase, FBXW7. Unfortunately, FBXW7 has other important substrates. The authors think they can make an inhibitor that only inhibits the FBXW7-DISC1 interaction but I am very skeptical of that. When do we see that in medicine? Anyone? Anyway, as far as target discovery from immunoprecipitation all the way to crystallography, Yalla et al do a tremendous job here.

Two Phase 3 Trials of Bapineuzumab in Mild-to-Moderate Alzheimer’s Disease. Salloway, et al. NEJM 2014;370:322-33.
Nothing to see here. Just another important history lesson in drug development.


Biopharma & Investing
A mega-price increase from a small company I had never heard of before: Aytu, who increased the price of their Ambien-containing nasal spray. This is actually a neat product, as some people have difficulty swallowing pills and it makes sense that a non-pill Ambien by the bedside may be easier to use. I once tried to buy a company (for $0 EV) called Transcept who made a ODT version of Ambien. That drug is now generic. If I worked at an HMO, I’d mandate people take that drug instead of the nasal spray. So, some price increases don’t work (or shouldn’t work). People who are on and are comfortable on this drug, however, are unlikely to be forced to switch. Maybe a higher copay (maybe much higher).

Beigene and Alnylam have similar valuations but extremely dissimilar prospects. Beigene is late-to-market in China for PD1 and extremely late to a crowded market in the US where they “share” economics with CELG. Their other drugs don’t target large markets. Alnylam has revolutionary technology which has proven successful in many clinical settings, with at least one drug that will sell well over $1 billion.

I’m starting to get worried about Bluebird. Wiping out your bone marrow and living in a hospital for 6 months may not be the cure for what ails you in the shadow of gene therapy for some illnesses and traditional modalities for others (sickle cell). But, BCMA!, you might say? Well, lots of companies have BCMA CART. The MM market is starting to worry me, too. We have lots of great drugs and we haven’t seen commercial success for CART yet. I’m starting to wonder about the upside here.

Some people want more from me on the subject of investing. I write this blog mostly for my teammates around the world who can study my notes and help my companies grow. I’m an unemployed passive investor, but if my philosophies and notes can be of use to someone, great. It’s free. I doubt I’ll give any structured theory of investing despite interest in a book on the subject. The grand unified theory for investing is still unclear to this observer, but I’ll share some explorations as they occur. I will probably write extensively on quantitative investing, value investing and other topics as time marches on.

One of my favorite questions in investing is how do you reconcile taxes in long-term market ‘expectations’? I, of course, believe that the expected median return for an individual global equity is actually negative. But if you are in the polyanna crowd, and you think for some insane reason that future stock performance will be 5% pa or something like that, how do you reconcile having to pay ~25% taxes (long-term rate) in the US? Does that make a 4% return a 3% return? How do you account for the asymmetry? And what about inflation, what is that really? In a world where the “price of goods and services” are irrelevant to a millionaire (any reasonable investor), shouldn’t the price of asset classes be your new inflation? After all, I’m not so worried about a tank of gas and a carton of milk. The prices of a Hamptons house and a La Ferrari are not in the current CPI basket, but your frame of reference is crucial to understanding inflation, in my opinion.

Anyway, if you believe, for whatever reason, that US stock markets going forward, measured by the S&P 500 index (implicit bias here, too), will average 5% per annum, what are you really getting? Well, you have to pay the 25% taxes, no matter what. I’m being generous as there are all kinds of hidden taxes, such as consumption tax, legal and accounting costs (which are, in essence, taxes). So that’s 3.75% net, but net of 2% inflation (whatever that is), you’re at 1.75% real returns. That’s including your massively foolish implicit bet that large-cap United States stocks have their best days ahead, as compared to say, China, India or any other country. You’d have to buy the Russell to avoid the large-cap bias, and perhaps hedge with international MNCs to avoid the US bias. If you could construct a basket of diverse market cap stocks, with their % of business in the US at perhaps 20%, you’d have a truly equity-like instrument. I think your performance net of inflation and taxes would be negative or zero. You might ask how this “system” could do anything but fall apart, in the long run. I’m not a perma-bear or anything like that. First, I don’t think expected return on equities is massively negative. Next, I think a large part of our financial system is constructed on a strange and amorphous foundation that still holds surprises for us. The stock market is ‘everything’ to so many, but real estate, private equity and other fields dwarf equities. Events in those markets impinge on stock performance such that sometimes its a good idea to pay $750 billion for $6 billion in annual (but growing!) cash flow and sometimes it isn’t. I’ll have more to say next time.

Papers I’ve Read
A Phase 3 Trial of Semagacestat for Treatment of Alzheimer’s Disease. Doody et al. NEJM 2013 369;4:341-350.
This is maybe the third time I’ve read this paper from 5 years ago. It’s rare in medicine to get a hypothesis so wrong that the drug does a statistically significantly WORSE job than placebo. This gamma-secretase “inhibitor” worsens cognition and functioning. Some believe it is in fact, not a gamma-secretase inhibitor, but I don’t agree. Peripheral reduction of the putative causative agent of Alzheimer’s, amyloid-beta, was seen, but CSF (no mention of cortical) amyloid-beta was not. Brain disease is region specific (paracrine) and that makes treatment quite difficult. For instance, hippocampal amyloid-beta may be harder to target than perhaps more vascularized areas of the brain. So what explains -9 ADL for placebo and -13 for drug, a palpably worse effect? Two possibilities come to mind.
First, this drug is inhibiting some enzyme that is causing the effect seen. Whether that target is gamma-secretase or not is an entirely different question. If it is gamma secretase, two more sub-questions result. 1) Does regiospecific inhibition explain this phenomenon? We have APP for a reason. It is possible APP aids cognition or synpatic function or something in one cortical area and is problematic when it aggregates in another (hippocampus, amygdala). Oxytocin, serotonin and other neurotransmitters work this way. 2) The second major question is this drug is inhibiting gamma-secretase but that is not the primary causal effect. Many enzymes like GSAP are in this cascade and enzyme conformation often is a signal onto itself for feedback purposes. Stopping gamma-secretase, which ordinarly processes (cleaves) a precursor protein (a common theme in peptide signal biology, see endothelin, angiotensin), may prevent a key feedback signal telling some gene to stop making APP, resulting in paradoxically greater APP. We see reductions in AB, so one is tempted to reject this hypothesis, but AB alone may not be the whole story.
If semagacestat’s target is not gamma-secretase, what enzyme is it, and how could it serendipitously have such a profound impact on cognition? This seems highly unlikely, and we should use this opportunity to probe semagacestat further to understand AD biology. We see immune changes with human dosing, raising the possibility that AD results from immune aging, a hypothesis that was once also speculated for cancer. With no CSF AB or PET changes, one still has to question target engagement for sema. The dosing of 100mg vs 140mg is terribly awkward and hardly seen in medicine. That we see an increase in AB40 and AB42 reduction at 140mg is somewhat puzzling. Why not 200mg? What is DLT here and where is it coming from? Everyone seems to be pointing the finger at NOTCH inhibition but would that really explain increased dementia? If so, why not reverse this process? How about some CSF PK data?
Anyway, this one is an important mystery for current, future and prospective drug hunters to look back on and learn from. A pharmacological mystery.

Phase 3 Trials of Solanezumab for Mild-to-Moderate Alzheimer’s Disease. Doody, et al. NEJM 2014 370;4:311-321.
A lot of observers felt Lilly could have filed and received approval for sola on these barely-missed Phase IIIs. Certainly they stoke the idea that beta-amyloid intervention in AD should begin as early as possible and tantalize potential benefit with predictive diagnostics. That EXPEDITION 2 wasn’t repowered for only mild disease is unfortunate, they probably would have met a primary endpoint. Then, EXPEDITION 3 failed. So, just remember that subgroups are still subgroups and even with an a priori mechanism of action, there is a bit of luck involved in these trials, and trying to squeeze out a really small treatment effect in a new trial powered for that small effect is likely to backfire. Why develop a drug that is, at best, a modest therapy? The lack of binding fibrillar AB probably did this one in. A prodromal study is ongoing, I believe.

Some people are interested in how sentencing works. Given that almost no one is a criminal defense attorney (a very tough job!), allow me to explain to the uninformed. In federal prison, there is no parole. “Good time” is roughly 15% of one’s sentence, assuming serious no violations (so far so good, on my end). However, the 15% is overstated, and actually works out to 13.8% or something like this. Some speculate that the entire 15% will be restored in a soon-to-come criminal justice reform. While I won’t hold my breath, you can look up and calculate the exact number of DAYS you would get on an 84 month sentence by statute. My attorneys and sentence consultant have done this, it’s around 12 months. As you may know, I was sentenced to 84 months, and as of two days ago, I have been in prison for 10 months, meaning I have 74 months to go. When you include “good time”, I would have 62 months left. We’ve only gotten started on calculating, however. Prisoners like me are able to do 10% of their sentence as “home confinement”, which would be 8.4 months. This option is not available to everyone, but for nonviolent crimes, it is available. It used to be 5% until very recently. Next, there is a program available to certain prisoners that reduces a sentence by 12 months. Finally, any half-way house time would overlap with home confinement time, but if greater than that time, would count. For instance, if halfway house of 12 months were assigned to a prisoner who had 8.4 months of home confinement time, that prisoner would simply get halfway house/home confinement of 12 months. So, 84 – 10 – 12 – 12 – 12 = 36. Of course, the final 12 could be as little as 8, and one of the 12s could be anywhere from 11.0 to 12.6. My lawyers and I are confident in those numbers, but the full range best case/worst case would be 35 to 40 months. So, I project I’m 37 months away from home at this time. I also have an appeal pending, don’t sleep on that 🙂 Anyone playing along at home is free to do their own calculations and comment on the site!

There’s a guy here who doesn’t know any Beatles songs. I think there are a few guys here. He wanted to know their most famous song. I said: “Yesterday, Hey Jude, Lucy in the Sky With Diamonds, err… Imagine? Yellow Submarine?”. Drew blanks. Did I miss one?

I think the left needs to talk about unity instead of resistance. I’d be willing to apologize to Lauren Duca for nagging and teasing her, apologize to Lena Dunham for offering to afford her private plane trip to Canada, and others. The right needs to reach across and stop the flame war, as fun as it is. People like Hannity, Carlson, Dinesh, Milo, any standard bearer for Republicans, should begin this process. If the left won’t agree to “lay down arms” and focus on strengthening our country instead of dividing us further, then their party will dwindle into irrelevance and implode in hatred (has it already happened?) But we shouldn’t follow that lead. Let’s find common ground and cease the incessant and overwrought narrative that everything left-of-center is malignant and everything right-of-center is righteous. My reasoning for this change of pace arises from witnessing the miserable sorrow of various pundits and commentators. Losing stinks, but cheer up. We can get through this together. We lose, too. Being happy is more important than having your life subsumed by complaining. You can be happy with Trump. I was happy with Obama. I was happy with Bush. I’m always happy because there are more important things than driving yourself (and others) crazy with politics. Some of us like politics, and are passionate about it, and that’s fine, too. But we can use a different, less inflammatory and flamboyant language to convey what we’re thinking. Sometimes the understated is far more effective than bombast.