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About the Author:
Tracy Marshbanks, Ph.D.
Managing Director
Tracy Marshbanks is a managing director. He works with companies in a variety of sectors, particularly businesses where chemical and medical technologies are a key differentiating element. He is a thought leader in his sectors, authoring research and using his industry knowledge and expansive network to uncover promising investment opportunities and help companies navigate their strategic paths and accelerate growth. Prior to joining First Analysis in 1999, he held a number of positions with Amoco Corp. with responsibilities ranging from refining research and development to capital planning (first in petroleum refining and then in marketing). He earned an MBA from the University of Chicago, a doctorate in chemical engineering from Purdue University, and a bachelor’s degree in chemical engineering from Colorado State University.
First Analysis Process Technology Team
Tracy Marshbanks, Ph.D.
Managing Director
Eric Terhorst
Senior Vice President
Matthew Nicklin
Managing Director
Joseph Munda
Vice President
First Analysis Quarterly Insights
Process Technology
Quants II: Drug discovery "rocket scientists" lifting off
January 25, 2021
  • Advanced data analysis, modeling, and model systems - quantitative domains that gained the moniker "rocket science" based on their successful and transformative application in aerospace - have also been successfully applied in several unrelated areas such as finance.
  • But while these rocket science tools and capabilities have long held great promise in the field of drug discovery, they have generally delivered marginal benefits. We contend that's because the complexity of the challenges posed by drug discovery and development (the complexity of biology) is orders of magnitude greater than in the areas where "rocket science" has historically seen success.
  • Today, we see advancements in science and technology we believe will enable the quant approach of using large amounts of quality data and analytics to more fully realize its potential in drug discovery and development. These advancements include large increases in computing power and scale and new tools for engineering and interrogating model biological systems.
  • We profile a handful of companies successfully applying today's rocket science to drug discovery and development with business models that extend beyond traditional fee-for-service to taking equity stakes in the therapeutic products they enable with their partners or undertaking proprietary therapeutic product development.

TABLE OF CONTENTS

Includes discussion of BTAI, CDXS, SDGR, SLP, Viva Biotech (1876.HK) and one private company

Drug discovery much tougher than rocket science, new tools just beginning to tackle the challenge

Traditional and newer business models capture the value of innovation

Some pioneers using drug discovery "rocket science"

Rocket science in drug discovery and development: Transforming our world again

Process technology index appreciation continues

M&A activity remains subdued

Q4 private placements accelerate

Introduction

The extraordinary returns recently seen among a number of our process technology universe public companies suggest something is afoot. A commonality among these companies is they are leveraging experimentation and analytics expertise (their "rocket science") to participate in the drug discovery and development market with models including 1) selling their services or access to their platforms on a fee basis, 2) taking equity stakes in the therapeutic products their capabilities enable, and 3) in some cases using their capabilities to develop their own drug pipeline. We believe these companies' strong stock price performances and associated eye-popping valuations reflect the long-term potential of this drug discovery "rocket science" - potential not captured in simple short-run valuation metrics. Table 1 shows how the market has ascribed billion-dollar-plus values to discovery technology companies with near-term revenue prospects measured in the tens or hundreds of millions and typically no expectation of near-term profit.

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