LIFE SCIENCES /// CLINICAL DEVELOPMENT

Address tumor heterogeneity and identify optimal responder patient populations to design clinical trials that enable the evaluation of safety and efficacy while also monitoring resistance mechanisms.

• Uncover real-world insights regarding patient demographics, treatment regimens, and outcomes to define I/E criteria and preliminary endpoints, as well as guide the selection of appropriate comparator therapies and inform decisions on trial design, dosing, and safety monitoring.

Optimize patient selection, monitor drug effects, assess safety, and predict treatment outcomes between trial phases to guide clinical decisions and support regulatory submissions.

• Enhance patient stratification through insights surfaced across multimodal datasets, further validating biomarkers by correlating them with real world clinical outcomes in various patient subgroups.
• Monitor treatment effects in real-time through a multi-omic approach to anticipate mechanisms of resistance.

Identify and enroll diverse patient populations, activate trial sites quickly, and maintain high-quality data collection protocols.

• Leverage real-world data to optimize study design and a vast provider network to select sites, accelerate activation, and algorithmically match potentially eligible patients for enrollment.
• Engage a strategic Contract Research Organization to manage trial operations from start to finish, including feasibility and planning, patient recruitment, and data collection across multiple sites.

Prioritize disease states based on therapeutic potential to address unmet patient needs and potential for regulatory and commercial success.

• Assess disease prevalence, patient demographics, treatment gaps, and current therapeutic outcomes across multimodal RWD cohorts to identify areas of high unmet need and evaluate clinical feasibility.
• Simulate disease mechanisms and drug interactions in tumor organoid models to evaluate treatment safety and efficacy of various indications.

Leverage a broadly distributed platform and a data-driven approach for IUO assay and companion diagnostic development.

• Analyze real-world evidence to understand biomarker prevalence and assess its predictive value in real-world settings to guide more effective patient selection for targeted therapies.
• Detect mutations, resistance mechanisms, and tumor heterogeneity to optimize for clinical utility through comprehensive genomic profiling.