By removing the need for placebo-controlled cohorts, they could reduce the number of participants needed for clinical trials.Īccording to the firm, digital twins can also increase study power by decreasing variability, as well as powering secondary endpoints and exploratory analyses and providing additional evidence to understand how each patient responded to an experimental treatment in a trial.Ĭurrently, the company is focusing its DiGenesis machine learning platform on Alzheimer’s disease and multiple sclerosis – diseases with few or no effective treatment options. ![]() Digital twins integrate data from real patients with the aim of replacing them in placebo control groups. In the context of clinical research, Unlearn explains, a digital twin is a “longitudinal, computationally generated clinical record that describes what would have happened if a specific patient received a placebo”. The firm claims to be the first to create ‘digital twins’ to populate intelligent control arms in clinical studies. Unlearn.AI is a San Francisco startup founded in 2017 by former Pfizer principal scientist Charles Fisher. The company is working with its biopharmaceutical partners to use their insights for clinical trials by identifying high-risk patients who might respond best to an experimental drug.Īs part of a long-running Series A funding round, the startup closed $18m from Mubadala Capital and Bpifrance in June 2020, bringing the total amount raised in the round to $70m. The company has a catalogue of over 70 life models built using both public data and its own and interpretable AI, which enables further research and the identification of new biological targets. ![]() ![]() Owkin harnesses federated learning to train and develop its machine learning models to increase clinical trial efficiency. Owkin is a pioneering French AI start-up founded in 2016 by Thomas Clozel and Gilles Wainrib and headquartered in New York.īased on a company mission to make clinical research more collaborative, the AI platform connects data scientists, clinicians, academic researchers and pharmaceutical companies to unlock medical insights from siloed, multimodal datasets and help pharma companies to discover new drugs and biomarkers, optimise clinical trials, and quickly identify patient populations of interest.
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