Innovation In Clinical Trials

What if you had insights from historical trials and real world data at your fingertips when designing clinical trials?

Today, pharmaceutical companies largely rely on institutional memory, medical expertise, and intuition to design clinical trials. We would like to change this.

We envision an integrated technology platform - with pre-built data ingestion pipelines, AI models, and an intuitive user experience - all built on AWS services.

  • Data Ingestion Pipelines - Ingest, integrate and standardize historical clinical trial scientific and operations data and real world data.
  • NLP Pipelines - Extract insights from historical clinical trial protocols, both from your internal repositories and industry databases such as the Clinical Trials Transformation Initiative
  • Predictive Models - Understand the impact of trial design decisions on downstream metrics such as feasibility, cost, cycle time, and quality risk (e.g., Predictive Site Health™, Patient Burden, Enrollment Timeline)
  • Intuitive User Interface - Manage your trial portfolio, build and optimize trial design scenarios and collaborate across the asset team

By making more informed decisions at the beginning of the clinical trial design and planning lifecycle, you can proactively help reduce the risk of costly delays and protocol amendments - ultimately accelerating time to market and bringing potentially life saving treatments to patients faster.

Capabilities we can help deliver

Digitize Protocols

With text extraction and NLP pipelines, make historical clinical trial protocols machine readable

Improve Eligibility Criteria

AI models help you see the predicted impact of your inclusion / exclusion criteria choices on screen failure rate, enrollment feasibility, and diversity

Improve Schedule of Activities

Predictive models help you understand the likely patient burden and cost of your trial and improve the schedule of activities accordingly, including activity virtualization recommendations

Select Countries & Sites

Optimization algorithms suggest a list of countries and sites for your trial, based on your prioritized metrics (e.g., enrollment speed, cost, quality risk, Predictive Site Health™, and diversity)

Impact of Intelligent Clinical Trial Design

Reduction in Trial Cycle Times

Revamp trial design to improve enrollment timelines and reduce likelihood of protocol amendments and delays

Reduction in Trial Costs

Improve schedule of activity design, country allocation, and site selection to reduce costs

Innovation with Data Driven Insights

Leverage insights from your trial archives and real world data to design trials that are hybrid or decentralized, explore master protocol usage and adaptive designs, and reach more diverse populations

Contact us

Matthew Rich

Matthew Rich

Principal, PwC US

Sidd Bhattacharya

Sidd Bhattacharya

Partner, PwC US

Eduardas  Valaitis

Eduardas Valaitis

Director, PwC US