Introductory resources for analyzing biotech clinical trial results (updated 3/28/24)
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If you work in or around biopharma, you need to know how to evaluate clinical trial results to be a star performer – there’s no getting around it. But what’s the best and most efficient way to learn to critically read press releases, investor presentations, conference presentations, and journal articles?
There’s no perfect “one-stop shop” to boost your skills in interpreting interventional drug trial results. (Well, there wasn’t … until I wrote one! See below.) But there are several fabulous resources available that, taken together, form a solid foundation – and several of them are free!
In this post, I’ve compiled some top recs for folks who want to get better at reading study reports on development-stage drugs and reaching their own conclusions. I think this list will be particularly useful for:
Biopharma folks in non-clinical functions – senior management, commercial, BD, preclinical research, etc.
Finance folks — investors, VCs, I-bankers, equity analysts, etc.
Consultants who advise biotech and pharma clients
Health care journalists
Prospective biotech entrepreneurs who don’t have deep backgrounds in clinical development
Academic physicians and scientists
Students and trainees in medicine, science, pharmacy, etc.
These resources are mainly aimed at less experienced folks, but many are also useful for mid-career pros looking to refresh or extend their knowledge. (I’ve been in this biz for a while, and I definitely learned a ton from them!) The main exceptions are professional biostatisticians and folks who routinely design and/or execute clinical studies; those individuals should definitely look elsewhere for more technically detailed materials.
Two final points: First – if your fave resource isn’t listed, please email me so I can check it out and possibly add it! (This version was last updated on Dec. 8, 2022.)
And second – if you’re interested in learning more about drug development, you’ll want to read THE PHARMAGELLAN GUIDE TO ANALYZING BIOTECH CLINICAL TRIALS. It’s a great resource for non-experts who want to get more confident analyzing biotech study results. Click here to learn more details, read endorsements from industry experts, and get a free excerpt, and when you’re ready, buy it on Amazon.
1. Basics of drug development and FDA approval pathways
First up are a few recs for the total newbies in the audience. If you’re a generalist investor just getting into biopharma, a finance pro who recently joined a biotech from outside the industry, or a student who’s just starting your biotech trials journey, you first need to get grounded in some basics about how a drug gets from the lab to the market. For many folks, the best intros will be the ones on the FDA’s website, where you’ll learn the basic differences between Phase 1, 2, and 3 studies, as well as the meanings of terms like IND and NDA that you’ll see in press releases and investor decks. You’ll also be able to dig into expedited approval pathways like Accelerated Approval, Fast Track, and Breakthrough Designation; although these aren’t directly related to the scientific aspects of clinical trials, they often have important impacts on how to put results in the broader context of a drug candidate’s path to patient care. There’s a ton of great basic info on the FDA website that’s worth checking out, but I’ve listed a few faves below to get you going.
2. Introduction to critical appraisal of clinical trials
Once you’ve finished the prerequisites, it’s time for your first intro to interpreting biotech clinical trial results. The overviews by Akobeng, Alderson, Govani, and Juni are great intros if you’re completely new to assessing trials. Afterwards, my next go-to rec is a series of articles from 2015 by Stuart Pocock and colleagues. Although it focuses on large cardiology studies and is now a tad dated, it provides a great framework to methodically assess the various components of a drug trial, including the population, endpoints, design, and results, and also points out many common “red flags”. Pair it with two essays by Pocock and Gregg Stone on interpreting positive and negative results, and you’ll be off to a great start.
“Understanding Randomized Clinical Trials” (Akobeng, Arch Dis Child; free)
“How to Critically Appraise a Research Paper” (Alderson, Paeds Child Health)
“How to Read a Clinical Trial Paper: A Lesson in Basic Trial Statistics” (Govani, Gastroent Hep; free)
“Assessing the Quality of Controlled Clinical Trials” (Juni, BMJ; free)
“Statistics for Clinical Trials” series (Pocock, JACC; free): Part 1, Part 2, Part 3, Part 4.
“The Primary Outcome is Positive – Is That Good Enough?” (NEJM; free).
“The Primary Outcome Fails – What Next?” (NEJM; free).
3. Basic clinical trial statistics
Once you learn the basics, it’s time to dig into the math. For non-statisticians starting out, this can be confusing and intimidating, and even though I learned a fair bit of stats “on the job,” I got a lot out of some focused self-study to consolidate my knowledge and fill gaps. Complete newbies might want to start with the first two books below, by MSKCC biostatistician Andrew Vickers and GraphPad founder Harvey Motulsky, respectively. Both are short, readable, entertaining, and aimed at non-experts, and neither requires any math beyond basic algebra. Motulsky also wrote a longer opus, Intuitive Biostatistics, which is a great “advanced beginner” resource that is still extremely accessible by non-statisticians with basic math chops.
For slightly more detail, The BMJ and JAMA have both addressed many stats areas in bite-sized articles of a few pages each. You’ll need to separate the wheat from the chaff, because these sources also address topics like retrospective studies and meta-analyses that aren’t relevant to clinical trials, but all of these are lucid, well-explained guides. Pair them with the books above, and you’ll be dropping phrases like “Bonferroni correction” like a boss in no time.
What is a P-Value Anyway? by Andrew Vickers: Amazon.
Essential Biostatistics: A Nonmathematical Approach by Harvey Motulsky: Amazon.
Intuitive Biostatistics: A Nonmathematical Guide to Statistical Thinking by Harvey Motulsky: Amazon.
BMJ “Statistics Notes” articles (1995-2018; free): Full archive here; easier-to-peruse list here.
JAMA “Guide to Statistics and Medicine” articles (2014-present; paywalled): Full archive here.
4. Clinical trial case studies and deep-dives
There’s no better way to get smarter about biotech clinical study results than to see how experts pick them apart. Some of the best case studies for learning to interpret drug trials are analyses by experienced biopharma journalists like Madeleine Armstrong (who also covers medical devices!), Adam Feuerstein, and Jacob Plieth. And among clinicians who opine on clinical trials, I learn a ton from cardiologist John Mandrola, whose work is very accessible, even to a non-heart specialist like me!
These folks get deeply into the weeds on clinical trial results, and their output is a great master class on how to apply general concepts to real-world situations, including not just full papers, but also press releases and meeting abstracts and presentations. I personally learn something new every time I read or listen to one of their posts. (To access articles by specific journalists, plug their names into the search bars of their respective outlets’ home pages.)
You should also check out Pharmagellan’s free email newsletter. About 1-3 times per month we discuss something about biotech clinical trials, usually anchored on a recent example. Topics have included endpoint switching, post-hoc subgroup analyses, and 1-sided P values. And did we mention that it’s free?
ApexOnco / Oncology Pipeline (Armstrong and Plieth; free).
Evaluate Vantage (Armstrong and Plieth through August 2023; free).
STAT (Feuerstein; paywalled) — make sure to check out Adam’s new “Biotech Scorecard” newsletter, which kicked off in March, 2024.
The Street (Feuerstein through mid-2017; free): if the whole archive is too overwhelming, consider starting with his “biotech stock mailbag” articles.
This Week in Cardiology blog and podcast (Mandrola; free): blog is essentially a transcript of the podcast, so pick your favorite format.
Pharmagellan email newsletter (free): sample issue (on red flags in biotech PR); sign-up form.
5. Our book on analyzing biotech clinical trials
Finally, a quick plug for our book. Intended for non-statisticians, THE PHARMAGELLAN GUIDE TO ANALYZING BIOTECH CLINICAL TRIALS is chock full of “news you can use” as you read drug companies’ press releases, conference abstracts, investor presentations, and publications. Key features include:
Structured roadmap for assessing the main components of a planned or completed biotech trial
Clear explanations of the most common concepts and terms in clinical studies, illustrated with over 100 real-world examples
Deep dives on essential topics like P values, sample size calculations, and Kaplan-Meier curves, written in plain English for non-statisticians
Pointers for interpreting positive and negative results, understanding common figures and tables, and identifying red flags in press releases
The book has gotten high praise from biopharma heavy-hitters like Adam Feuerstein of STAT, Sir Mene Pangalos of AstraZeneca, Daphne Zohar of PureTech Health, Michael Rosenblatt of Flagship Pioneering, and Dan Lepanto of SVB Leerink’s M&A team. Click here to read their comments and find out how to get a free excerpt. And if you want to buy it, just hop over to Amazon!