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Simbec-Orion. (10/26/23). "Press Release: Simbec-Orion and Launch Strategic Partnership to De-risk Early-stage Drug Development with AI Supported Clinical Trial Design". London.

Organisation Organisation GmbH
Products Product clinical research services
  Product 2 AI-based drug discovery / AI-based drug development
Person Person Klinger, Jörn ( 202310 CEO + Co-Founder formerly Beroceutica GmbH 201606– Managing Director + Co-Founder)

Simbec-Orion, a full-service mid-size CRO, and, a developer of AI-enabled causal modelling for drug development, have announced their strategic partnership to bring AI-powered insights and predictive models to support data-driven clinical trial design.

Simbec-Orion, a specialist in oncology, rare disease, and clinical pharmacology studies, has over 45 years' experience supporting biotech and small to mid-sized drug development companies with complex early-stage clinical development in highly competitive and specialist patient populations.

Fabrice Chartier, CEO at Simbec-Orion, commented:

"We are delighted to announce our strategic partnership with's data-driven predictions will offer our clients a cost-effective way to generate additional data to support their clinical development strategy, by utilising causal AI models to predict clinical trial outcomes and using these insights to inform clinical trial design."'s causal AI technology accurately simulates the outcomes of clinical trials using their extensive human genetic database, which contains 3.3 million cases spanning over 12,000 diseases, each with a full phenotype analysis. The accuracy of their causal AI has been demonstrated by successfully predicting the outcomes of eight different COVID-19 trials and has since been replicated across a range of indications and therapeutic areas.

Joern Klinger, CEO at, commented on the potential causal models offer when applied to clinical drug development:

"Causal models at scale enable drug development: For a given drug we find all mechanisms and diseases causally affected by it. We find the best indication for our client's drug, provide evidence for the absence of specific side effects compared to competing compounds, and, most importantly, evidence for the efficacy of their compounds in humans. For several of our clients this has been instrumental to successful fundraising for their phase 2 trials."

On the value of utilising AI-powered causal models to secure funding, Fabrice Chartier adds: "It is a highly competitive environment for biotech companies. Investors are demanding more data, and being more selective with the projects they choose to fund. We support clients at those crucial early development stages, using our knowledge and experience to help inform their clinical development and corporate strategy. Offering our clients an opportunity to gather data on predicted clinical trial outcomes, before reaching the clinic, is a valuable tool to demonstrate a drug's true potential to investors. With this technology, we can also provide input endpoints and protocol design to maximise the chance of delivering a successful study."

To learn more about Simbec-Orion's capabilities and experience, visit

About Simbec-Orion:

Simbec-Orion is a responsive and agile full-service CRO with specialist expertise in clinical pharmacology, oncology, and rare diseases. Perfectly structured to support small to mid-size biotech companies, Simbec-Orion provides full-service clinical development services with a focus on tailormade and scalable solutions. Experts in early clinical development, Simbec-Orion utilises over 45 years of experience to develop bespoke strategies which support each client's clinical and commercial objectives. Simbec-Orion is headquartered in the UK, with offices in Europe and the US. For more information, visit

For media enquiries, email or call +44 (0) 1753 989003

About are the first to apply causal modelling in drug development at scale. At its core, causal modelling mimics prospective, randomized clinical trials in large retrospective data – the genomes and full phenotypes and medical histories of 3.3 million patients. This allows for fast predictions of clinical success with huge statistical power, and, at scale, enables the discovery and validation of every mechanism and disease affected by a given drug. In practice has enabled clients to secure funding, explain the biology of their drugs and improve the design of their clinical trials. For more information, visit

Record changed: 2024-01-20


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