Chronic Obstructive Pulmonary Disease

Pre-Clinical

Challenge:

Develop a novel compound as a second-line therapy for COPD and investigate mechanistic rationale for possible efficacy/safety advantage vs. competitor

Approach:

Integrate preclinical & clinical information into a COPD PhysioPD Platform, simulate compounds, compare clinical outcomes and biomarkers

Results:

Showed novel compound efficacy to be inferior to competitor under current understanding of mechanism of action (MOA). Demonstrated that the novel compound’s MOA must include additional effect(s)

Impact:

Identified new MOA hypotheses and client initiated experiments to test hypotheses. Avoided possible risks of advancing compound into clinical development with incomplete MOA understanding

Oncology

Phase 1

Challenge:

Identify optimal dose and dosing schedule for a novel oncology antibody therapy with multiple mechanisms

Approach:

Built Platform to identify sensitive pathways in a growth factor-expressing tumor. Simulated treatment with antibody therapy and evaluated impact of dose and schedule variations on sensitive pathways

Results:

Identified key drivers of therapeutic response. Underlying patient characteristics (effector : target cell ratio) had greater impact than variations in drug dose and schedule

Impact:

Increased confidence in clinical trial design and identified potential biomarkers to guide patient inclusion criteria

Cardiovascular Disease

Phase 2

Challenge:

Select next generation compound with optimal binding properties. Translate in vitro results to in vivo animal and human efficacy to inform program decisions for next generation compound advancement

Approach:

Developed CVD Platform of in vitro and in vivo receptor binding and trafficking. Simulated multiple virtual compounds, varying binding properties, to evaluate efficacy

Results:

Identified optimal properties for next generation compounds. Enabled translation of results in vitro to primate and human paradigms

Impact:

Enabled identification and selection of next generation compounds. Informed decision-making using rigorous quantitative estimates of compound efficacy

Type 2 Diabetes

Phase 3

Challenge:

Drug with poorly characterized MOA showed reductions in A1C and plasma glucose. FDA review indicated a perceived inconsistency between A1C and average plasma glucose changes with no obvious explanation

Approach:

Develop a type 2 diabetes PhysioPD™ Platform including Virtual Patients consistent with client Phase 3 trial data. Generate hypotheses to explain observed relationships between A1C and glucose

Results:

Sampling time of fasting plasma glucose likely contributes to the perceived mismatch between A1C and glucose. Variability in dietary carbohydrate between clinical trial sites may impact observed response

Impact:

Informed client strategy for planned FDA discussions. Recommended strategies for future T2D drug trial design

Oncology

Phase 4

Challenge:

Gain a better understanding of response to current treatments. Guide the selection and development of new treatments

Approach:

Developed a PhysioMap®, capturing pathways involved in disease progression and current Standards of Care (SoC). Created a model framework for simulating treatment with SoC and investigational therapies in Virtual Patients

Results:

Gained insight into key disease-related pathways likely to control patient response and non-response

Impact:

Created a systematic, quantitative methodology to explore new treatments. The PhysioPD Platform can be integrated into the patient-specific Systematic Treatment Methodology.