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Empowering clinical operations and clinical development to improve trial design
Clinical trials are costly endeavors that often run over budget due to delays in patient enrollment. There are a multitude of factors that cause delays, such as a lack of available patients, high competition for patients/physicians, and clinical trial site fatigue to name a few. Innoplexus’ technology empowers clinical trial coordinators to identify centers likely to have untapped patient populations and underutilized emerging key opinion leaders interested in clinical trial research. Our AI technology accomplishes these feats via network analyses that connect diverse data points to provide insights not otherwise feasible and expedite clinical trials.
Innoplexus’ AI–powered solutions
- Identify Clinically-Oriented KOLs
- Predict Clinical Trial Outcomes
- Optimize Clinical Trial Design
- Clinical Trial Comparator
Access untapped KOL networks. Identify Top vs. Emerging KOLs and filter them by therapeutic area, location, publications, clinical trials, relationships with pharmaceutical competitors, and numerous customizable filters. Determine which KOLs to engage with based on four KOL archetypes Innoplexus has identified: Commercial, Clinical, Thought-leaders, and Public Speakers.
Accelerate the development of robust clinical trials by quickly comparing trials from over 100+ databases, including clinicaltrials.gov. Connect the outcomes of clinical trials, such as progression to subsequent phases, regulatory approval, and payer decisions with the trial parameters such as trial duration, sample sizes, endpoints, inclusion / exclusion criteria and others to determine the optimal trial design.
Compare running and completed (successful and failed) clinical trials in DLBCL and similar indications across a number of parameters. Get continuously Leveraged updated dashboard information in real-time, ensuring clinical trial design decisions are based on the latest information. Determine an optimal trial design to help ensure that the trial’s endpoints are clinically significant. Generate automated meta analysis and provide actionable insights, thereby greatly reducing time and unnecessary complexity.
Case studies & capabilities
Site Optimization & Enrollment
Identify trial sites & patient enrollment across various parameters
- Evaluating trial sites based on a client-specific filter system
- Identifying & segmenting KOLs across asset classes and involvement
- Integrating third-party and enterprise data to gain unique insights
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