February 2, 2019 –

WuXi NextCODE’s Tom Chittenden Named to Top 100 AI Leaders List

Tom Chittenden, head of WuXi NextCODE’s AI team, was recently named one of the “Top 100 AI Leaders in Drug Discovery and Advanced Healthcare.” Analysts at Deep Knowledge Analytics drew up the list from a pool of several hundred renowned scientists.

Tom Chittenden, head of WuXi NextCODE’s AI team, was recently named one of the “Top 100 AI Leaders in Drug Discovery and Advanced Healthcare.” Analysts at Deep Knowledge Analytics drew up the list from a pool of several hundred renowned scientists.

This is an extremely proud moment for all of us at WuXi NextCODE. Dr. Chittenden, PhD, DPhil, PStat, is our vice president of Statistical Sciences as well as founding director of the Advanced AI Research Laboratory. Started in 2015, the lab specializes in using analytics, such as machine learning (ML) and AI, to draw insights about causal genomic variants.

“This recognition reflects the remarkable work that all the lab’s team members, past and present, have contributed,” says Chittenden. “Since the field is just taking off, we are trying to help establish guiding principles through meticulous research methods and publications In leading peer-reviewed journals.”

Chittenden’s team has already worked on studies published in Science and Nature. The former examines somatic mutations in single neurons while the latter describes a previously unknown role of FGF in metabolic control of vascular development. Several more studies are in the works.

The list was compiled to provide: a “bird’s view” on the global leadership scene in the area of adopting ML/AI-driven methods in drug discovery and healthcare to serve as a benchmark tool for shaping successful talent acquisition strategies. Forbes contributor Yiannis Mouratidis wrote that “The profile of these people [on the list] is quite interesting: The majority (43%) were in academia or at AI-focused firms (30%).”

“With his deep experience in both advanced analysis and biology, Tom is exceptionally well positioned to lead our team in applying AI to drug discovery using genomics and other -omic information,” says WuXi NextCODE CEO Rob Brainin. “That gives them a much better chance of finding truly causative signals of biological importance.” Also, through its network of global partnerships WuXiNextCODE is creating a rich data set of multi-omics and deep phenotypic information to fuel its AI work and ultimately enable accelerated genomically-driven drug discovery.

Many experts are predicting that AI will be one of the strongest technological forces impacting key fields, including drug discovery and development. PricewaterhouseCoopers (PwC) analysts estimate that artificial intelligence could add $15.7 trillion to global GDP by 2030.

“The demand for the ML/AI technologies, as well as for ML/AI talent, is growing in pharmaceutical and healthcare industries and driving the formation of a new interdisciplinary industry (‘data-driven healthcare’),” the Deep Knowledge Analytics authors wrote about their report. As a result there are also a growing number of AI startups and companies offering related technology solutions for drug discovery and healthcare.

“It is an extremely exciting time for this field and we are honored to be among the leading pioneers helping to shape it,” says Chittenden.

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