Anagenex, a pioneering drug discovery company pairing large-scale data generation with machine learning to discover the next generation of small molecule medicines, today announced the appointment of Ryan Kruger, PhD, as Chief Scientific Officer. He brings 18 years of combined pharma and biotech experience, including 15 years at GSK, to his new role where he will be leading Anagenex’s scientific and drug discovery strategy from target selection to compound development. He will also be guiding technology development to reinforce Anagenex’s combined parallel biochemistry and AI platform.
At GSK, Kruger was Vice President, Head of the Cancer Epigenetics Research Unit, Oncology R&D where he was involved in the discovery and development of an industry-leading pipeline of epigenetic assets. During his time at GSK, his research unit brought forward six novel small molecule therapies from discovery, through IND filing, and on to clinical development. Kruger has also been a co-author on over 50 peer-reviewed scientific journal articles.
After leaving GSK, Kruger served as Vice President, Head of Biology at Foghorn Therapeutics, a clinical-stage biotech. At Foghorn he led a team of biologists, bioinformaticians, and pharmacology scientists through all aspects of discovery biology and early translational medicine, from new target ID and validation through early clinical development. Kruger earned his PhD in Pharmacological Sciences at the University of Pennsylvania and completed his postdoctoral training at Harvard Medical School.
“The most important thing for a technology-first drug discovery company is to know where to aim the platform for maximum impact,” said Nicolas Tilmans, CEO of Anagenex. “Ryan has a truly exceptional understanding of the biochemistry behind disease, and his leadership will ensure that our efforts will connect to patients in need. I’m overjoyed to have him join us on this journey.”
“I’m excited to join Anagenex, which has enormous potential to reshape how small molecule drugs are discovered,” said Kruger. “The synergy between machine learning and DNA Encoded Libraries differentiates the company, allowing us to reliably identify bioactive compounds and validate our disease hypotheses with unprecedented speed. Anagenex has the tools to address some of the hardest targets in drug discovery. I am also incredibly encouraged by the high quality of the Anagenex team.”
Since beginning operations in the fall of 2020, Anagenex has built a customized parallel biochemistry platform capable of generating billions of experimentally measured datapoints. Instead of relying on simulations, Anagenex’s proprietary machine learning (ML) algorithms can rely on real data and reinforce its understanding of each target by drawing from an internal database of hundreds of billions of previous measurements.
Anagenex then uses the trained ML models to design up to 1 million entirely new, “evolved” compounds, which Anagenex then synthesizes and tests before showing the results to the initial model, further refining its accuracy. This creates a virtuous cycle of real data perfecting ML models, in turn, driving better data generation, with each cycle honing in on highly selective, potent medicines.
By applying its platform, Anagenex has already developed a strong pipeline, including several early-stage drugs for oncology and other indications.
For more information about Anagenex, go to www.anagenex.com.
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