Estimated end-to-end cost of developing a new medicine.1
Academia · Industry · Healthcare · Regulatory science
Advancing the future of clinical development through AI
ClinSilico is a pre-competitive consortium uniting industry, academia, healthcare and regulatory science to develop and validate AI and in-silico tools for more efficient, evidence-driven clinical.
ClinSilico operating model A continuously learning system
01
Real-world data & historical trial data
Shared models & methodologies
03
Four integrated tools
Twins™Recruit™Adaptive Design™Agents™
04
Scientific evaluationEvidence & Validation
05
Clinical applicationClinical development & deployment
Regulatory science embedded throughout
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Continuous learningNew evidence informs refinement and revalidation
About ClinSilico
A continuously learning system for clinical development
Clinical development remains expensive, lengthy and complex. Valuable evidence from completed trials is often fragmented across organisations, limiting opportunities to learn collectively.
ClinSilico aims to bring appropriately governed historical trial, clinical and research data into a pre-competitive programme that develops shared AI models and tools around common priorities.
Independent validation and regulatory science will inform development from the outset. Following appropriate validation, deployment evidence can support further model development and revalidation.
By learning from existing clinical trial data and applying advanced AI and statistical methodologies, ClinSilico aims to support more efficient, inclusive and evidence-driven clinical development.
01Data sharing
02Model development
03Tool development
04Validation
05Deployment
Data can remain within approved environments under its custodian’s control, with permitted model updates and results combined securely.
The Power of Collaboration
The challenge is shared.The solution should be too.
Developing new medicines remains expensive, lengthy and complex. Across the pharmaceutical industry, organisations face many of the same challenges, yet the data, expertise and resources needed to address them remain fragmented.
ClinSilico brings industry, academia, healthcare and regulatory science together to build the shared foundations for AI-enabled clinical development.
Industry estimates
Of clinical trials are delayed or closed due to recruitment challenges.2
Sources: 1 Deloitte, Measuring the return from pharmaceutical innovation. 2 Tufts Center for the Study of Drug Development, Tufts CSDD Impact Report (2013).
Why work together?
01
Broader, more diverse data
Combining historical trial and real-world data across organisations enables the development of more representative and generalisable AI models.
02
Shared expertise & investment
Bringing together AI, clinical, statistical and regulatory expertise allows partners to share costs, accelerate development and avoid duplicating effort.
03
Shared evidence & trust
Collaborative validation and regulatory science help establish common approaches to evidence generation, transparency and responsible clinical use.
04
Continuous learning
Shared models and methodologies can be refined using new evidence from across the consortium, creating a foundation that improves over time.
Our Technology
Four integrated tools. One shared vision.
We envisage four complementary AI-enabled tools, built on a shared data and modelling foundation. Their scope and development priorities will be shaped collaboratively with consortium partners.
01
ClinSilicoTwins™
Digital twins for clinical development.
Developing patient-level, population-level, trial-level and development-environment digital twins to support in-silico reasoning, treatment response and safety assessment, trial simulation and evidence generation.
Proposed capability
02
ClinSilicoRecruit™
AI-enabled patient recruitment.
Using biological, clinical, trial and real-world data to identify relevant patient populations, improve recruitment feasibility, support site selection and optimise recruitment strategies.
Proposed capability
03
ClinSilicoAdaptiveDesign™
Intelligent trial design and optimisation.
Developing statistical and AI-enabled methodologies to support trial design, dose optimisation, cohort enrichment, adaptive trial strategies and evidence-based decision-making.
Proposed capability
04
ClinSilicoAgents™
AI agents for clinical development.
Developing AI agents to integrate evidence, identify fragile assumptions, stress-test trial designs, connect relevant data streams and support clinical development teams with appropriate human oversight.
Proposed capability
These tools represent proposed development directions. Their scope, functionality and priorities will be refined with consortium partners, with appropriate validation and regulatory alignment for each intended use.
The Consortium
Bringing together expertise across science, healthcare, industry and regulation
ClinSilico brings together five founding delivery partners, combining world-leading expertise in artificial intelligence, clinical trials, statistical methodology, regulatory science and pre-competitive collaboration. Together, they provide the scientific, clinical and organisational foundations to develop, validate and deploy AI-enabled tools for clinical development.
01
Cambridge University Health PartnersProgramme leadership, strategic partnerships and access to Cambridge’s academic, clinical and life sciences ecosystem.02
Cambridge Centre for AI in MedicineAcademic leadership in artificial intelligence, causal modelling and digital twins, including pioneering research led by Professor Mihaela van der Schaar.03
MRC Biostatistics UnitLeadership in clinical trial design and advanced statistical methodology, bringing extensive experience in clinical trials, adaptive designs and the development of robust evidence for clinical decision-making.04
UK Centre of Excellence on In-Silico Regulatory Science and InnovationRegulatory science expertise supporting the development, validation and evaluation of in-silico evidence and regulatory-aligned methodologies.05
Pistoia AllianceIndustry convening and a trusted framework for pre-competitive collaboration, bringing pharmaceutical and technology companies together to develop shared solutions to industry-wide challenges.
Cambridge University Health PartnersProgramme leadership, strategic partnerships and access to Cambridge’s academic, clinical and life sciences ecosystem.02Cambridge Centre for AI in MedicineAcademic leadership in artificial intelligence, causal modelling and digital twins, including pioneering research led by Professor Mihaela van der Schaar.03MRC Biostatistics UnitLeadership in clinical trial design and advanced statistical methodology, bringing extensive experience in clinical trials, adaptive designs and the development of robust evidence for clinical decision-making.04UK Centre of Excellence on In-Silico Regulatory Science and InnovationRegulatory science expertise supporting the development, validation and evaluation of in-silico evidence and regulatory-aligned methodologies.05Pistoia AllianceIndustry convening and a trusted framework for pre-competitive collaboration, bringing pharmaceutical and technology companies together to develop shared solutions to industry-wide challenges.Cambridge’s scientific and clinical ecosystem
Depth of expertise, connected by a shared purpose
- MRC Toxicology Unit — mechanistic toxicology and safety
- Cambridge’s clinical and academic research infrastructure
- Secure data environments and high-performance computing
Industry partners
Shape the questions that matter
Pharmaceutical and technology partners can help shape priority use cases, contribute relevant data and scientific expertise, share development costs and benefit from a common foundation they can adapt to their own needs—without giving up their commercial independence.
Responsible Innovation
Responsible innovation, embedded from the outset
ClinSilico aims to develop AI technologies that are scientifically robust, ethically responsible and informed by the needs of patients, clinicians and regulators.
Patient and public involvement
Putting patients at the centre
Patient and public perspectives will inform ClinSilico through POPPED, the Cambridge-developed involvement and engagement platform led by Dr Ben Underwood and colleagues.
This expertise will help shape research priorities, tool development, acceptable uses of data and the evidence needed to build trust in AI-enabled clinical trials.
Visit POPPEDAI ethics
Ethics by design
Professor Barbara Pierscionek brings expertise in AI ethics and the ethical and legal considerations surrounding emerging technologies.
Her contribution will inform transparency, accountability, fairness, data governance, human oversight and responsible deployment throughout the programme.
Meet Professor Barbara PierscionekRegulatory science
Building evidence for real-world use
UK CEiRSI will bring regulatory science expertise to help define validation requirements and generate evidence for assessing ClinSilico tools in specific clinical development applications.
The consortium aims to work with relevant regulatory stakeholders to develop credible evidence and evaluation frameworks.
Visit UK CEiRSIScientific rigour, patient trust and responsible innovation are fundamental to ClinSilico’s approach to AI-enabled clinical development.
Research & Insights
Research, publications and insights
Featured webinar
AI in Clinical Trials: From Promise to Practice
Hosted by the Pistoia Alliance
Explore the ClinSilico vision and how pre-competitive collaboration can accelerate the development of AI-enabled tools for clinical trials.
Watch the webinarFeatured scientific publications
01
From AI Methods to Clinical-Trial Transformation: Ten Years of Research at the van der Schaar Lab
02
Clinical Trials as Continuously Learning Systems
03
Automatically Learning Hybrid Digital Twins of Dynamical Systems
04
SyncTwin: Treatment Effect Estimation with Longitudinal Outcomes
Get Involved
Help shape the future of clinical development
Joining ClinSilico is an opportunity to help build a shared, pre-competitive foundation for the next generation of clinical development—not simply to sponsor an individual research project.
We welcome discussions with pharmaceutical and technology companies, CROs, academic researchers, clinical organisations and potential funding partners interested in contributing to the consortium while pursuing their own priorities.
Industry partnership Scientific collaboration Clinical collaboration Funding partnership
Get in touch
Interested in partnering with ClinSilico or contributing to the consortium? We’d love to hear from you. Complete our short enquiry form to tell us about your organisation and how you would like to get involved.
Complete enquiry formYou will be redirected to Microsoft Forms to complete your enquiry securely.