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    • Drug Combinations
    • Indication Expansion
  • Team
  • Contact Us

We help pharma companies with real world evidence-based insights applying our proprietary data platform & tool suite for biomedical and clinical data analysis Clinical Development & Outcomes Research

Slide Data to Knowledge to Insights

Slide Combining Real World Evidence with Biomedical Knowledge

Slide MOST CANCER CLINICAL TRIALS FAIL TO MEET ENDPOINTS DUE TO THE HIGH VARIABILITY BETWEEN PATIENTS AND TUMOR. BIOXPLOR APPLIES ITS PROPRIETARY PLATFORM TO COMBINE REAL WORLD EVIDENCE, CLINICAL TRIALS DATA AND MEDICAL LITERATURE TO DISCOVER NEW INSIGHTS WHICH CAN BETTER DEFINE PATIENT POPULATIONS FOR IMPROVED SUCCESS IN CLINICAL DEVELOPMENT AND OUTCOMES RESEARCH. THIS APPROACH IS APPLIED TO SECONDARY ANALYSIS OF CLINICAL TRIALS DATA AND TO REAL WORLD EVIDENCE TO IDENTIFY ENHANCED RESPONDER & NON-RESPONDER SIGNALS FROM CLINICL DATA. Enhanced Clinical Responder Analysis

Slide Network Pharmacology is an emerging field based in systems pharmacology that looks at the effect of drugs on both the interactome and the diseasome. The drug-target network (DTN) can play an important role in understanding the mechanisms of action of approved and experimental drugs. With a network-based insight, network pharmacology intends to systematically reflect and reveal the biological foundation of complex diseases and drug effects. The unique network-based relationship that drug pairs with Complementary Exposure to the disease module tend to be effective drug combinations is consistent with the non-overlapping pharmacological principle in rational drug combination design (Yıldırım et al., Nature biotech (Nature biotechnology (119–1126), 2007). Synergistic Drug Combinations

Slide Indication expansion (drug repurposing / drug repositioning) is a compelling lifecycle management strategy which can provide extended patent protection and market exclusivity, while increasing franchise revenues mid-lifecycle. However, extending indications has been associated with high costs and high risks due to the requirement for additional clinical trials. Applying data-driven approaches to prioritizing indications can mitigate these risks and costs considerably. Network pharmacology is a systematic methodology using a human protein-protein interactome, which prioritizes disease protein networks and drug target networks, based on efficacy and safety insights. The data-driven approach combined with validation of prioritized indications in cell and animal models, reduces costs up to 70% and improves timelines by 10x. Systematic Indication Prioritization
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