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Unlearn Signs Multi-Year Collaboration with Merck KGaA, Darmstadt, Germany to Accelerate Immunology Trials using Twintelligent RCTs™

February 16, 2022 – Clinical Trials –

San Francisco, Calif. – February 16, 2022 – Unlearn, developer of the Twintelligent RCT™, today announced that the company has entered into a multi-year collaboration with Merck KGaA, Darmstadt, Germany to accelerate late-stage clinical trials with novel trial designs that include Digital Twins. Initially, the collaboration will focus on advancing the regulatory approval of candidates in Merck KGaA, Darmstadt, Germanyís immunology pipeline, with the potential to expand into other therapeutic areas.

Unlearn works with pharma, biotech companies, and academic researchers to optimize human clinical trials by applying cutting-edge artificial intelligence methods to historical patient data. The company generates Digital Twins, which are comprehensive, longitudinal predictions of a patientís prognosis on a control treatment. Integrating Digital Twins into clinical trials is expected to reduce the required number of patients needed to be enrolled while enabling unbiased estimates of treatment effects. Unlike existing methods such as external control arms, the method Unlearn has developed, to incorporate Digital Twins into Twintelligent RCTs™, does not introduce bias and maintains randomization, two aspects critical to regulators. Using Twintelligent RCTs™, Merck KGaA, Darmstadt, Germany plans to incorporate prognostic information from Digital Twins into its randomized controlled trials to enable smaller control groups and generate evidence suitable for supporting regulatory decisions.
‘We are very pleased to establish this collaboration with Merck KGaA, Darmstadt, Germany and to be working with its world-class team who shares our vision for how AI and other innovative technologies can expand access to new medicines,’ said Charles Fisher, Ph.D., founder and CEO of Unlearn. ‘Our solution has successfully proven that it can reduce the size of control arms by 30% or more and generate reliable clinical evidence in a fraction of the time.’

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