The Pharmagellan Guide to Analyzing Biotech Clinical Trials - by Frank S David (Paperback)

About the Book

Called "the best explainer I've ever seen" by Adam Feuerstein of STAT, The Pharmagellan Guide to Analyzing Biotech Clinical Trials is a comprehensive primer, with 100 real-world examples, to help non-experts evaluate new therapies.

Book Synopsis

If you work in or around biotech, you're supposed to understand clinical trial results. But what if you're not an expert in study design or biostatistics? You may feel out of your comfort zone when faced with a journal article, press release, or investor presentation.

The Pharmagellan Guide to Analyzing Biotech Clinical Trials is a comprehensive primer to help non-experts evaluate clinical studies of new therapies.

• Structured roadmap for assessing the main components of a planned or completed biotech trial.
• Clear explanations of the most common concepts and terms in biotech 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 study results, understanding common figures and tables, and identifying red flags in press releases.

If you're a biotech executive, investor, advisor, or entrepreneur - or aspire to be one - this handbook will give you the foundation you need to analyze planned and completed clinical trials with more confidence.

Review Quotes

"The Pharmagellan Guide to Analyzing Biotech Clinical Trials is an indispensable research tool. This excellent book belongs on the desk of anyone involved-directly or tangentially-in the biopharma industry. With exhaustive research and clear language, this is the best explainer of biotech clinical trials I've ever seen. It spills all the secrets to clinical trial analysis! Now everyone will know how to do it well, and my job will be in jeopardy. Buy this book; you'll be smarter for it."

-Adam Feuerstein, Senior Writer, STAT

"This is a hugely helpful book highlighting the ins and outs of drug development, trial design, and data interpretation. I wish I'd had a book like this earlier in my career."

-Sir Mene Pangalos, Executive VP, Biopharmaceuticals R&D, AstraZeneca

"The Pharmagellan Guide to Analyzing Biotech Clinical Trials is a terrific primer for those looking to better evaluate new therapies. Readers get the tools they need to make informed decisions about the data and identify potential red flags. This is a must-read for non-experts to level up your understanding of drug development."

-Daphne Zohar, Founder and CEO, PureTech Health

"The biotech sector is booming, and during the pandemic we've witnessed its impact on health globally. Never before have so many people learned so quickly about the importance of clinical trials and been confronted with learning the process for demonstrating the safety and efficacy of drugs and vaccines. The Pharmagellan Guide to Analyzing Biotech Clinical Trials is a special resource for interpreting the results of clinical trials. It can be used to learn about the field all in one place, or as a refresher, or as a reference for looking up specific topics. This book is a crisp and clear explainer of key concepts in clinical trials, without a flood of detail on statistical methods (those are available through an extensive reference list). And the reader will find wise advice on when to rely on clinical data and when to be skeptical. I enthusiastically endorse this guide for biotech management, investors, bench scientists, journalists, or anyone interfacing with the world of biopharma clinical trials."

-Michael Rosenblatt, Senior Partner, Flagship Pioneering

"If you have struggled, like me, to make sense of the disconnect between the celebratory tone of a press release and the concomitant negative stock market reaction, The Pharmagellan Guide to Analyzing Biotech Clinical Trials is a source of much-needed illumination."

-Dan Lepanto, Senior Managing Director, M&A, SVB Leerink