Global Business Reports


Lucrezia Falcidia, Jason Spizer

AI in the Life Sciences 2020

October 01, 2020

When MIT mathematician Jim Simmons founded Renaissance Technologies in 1988, it was unfathomable that computers driven by algorithms might outperform top Wall Street fund managers. Today, after a more than thirty year average return of 66% per annum, the Renaissance model of applying machine learning techniques to invest in a manner that is automated, dispassionate and performed with minimal human intervention is widely accepted. Quantitative finance, as it is dubbed, has profoundly reshaped the financial industry.

In the past, pharma has expressed a similar skepticism around the adoption of artificial intelligence and machine learning to perform tasks such as molecular design, discovery and clinical trials. After all, lives are at stake and Mark Zuckerberg’s idea that success requires startups to “move fast and break things” is the antithesis of the industry’s guiding principle to “do no harm.” Despite this reluctance, there has been an explosion of promising startups created over the last five years that merge the field of computer science with computational biology, chemistry and biophysics. These companies are seeking to disrupt the current paradigm wherein new drugs fail to reach the market over 90-95% of the time, cost an average of US$2.6 billion to develop, with typical development timelines of 10-15 years.


Quartic AI explains how artificial intelligence and machine learning should be applied in life sciences.
Powered by its XmAb antibody engineering platform, Xencor is developing a broad pipeline of drug candidates that are optimized to treat autoimmune disorders, cancer, asthma and allergic diseases.
Tango Therapeutics is targeting unaddressed disease mechanisms in cancer to develop transformational new drugs for patients.
Founded in 2008, Eiger BioPharmaceuticals is a late-stage biopharmaceutical company focused on developing and commercializing targeted therapies for rare diseases.


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