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

Respiratory

Pre-Clinical

Challenge:

To anticipate possible adverse drug reactions, a client requested clarification of the mechanisms which induce and sustain bronchoconstriction in asthma patients

Approach:

Research was conducted in a Respiratory PhysioPD™ Research Platform representing a pulmonary neuromuscular junction, the effects of a methacholine (MCh) challenge, and the impact of inflammation on FEV1 (Forced Expiratory Volume) response to the MCh challenge

Results:

An analysis of the bronchoconstriction mechanisms and simulation of the Platform clarified the role of endogenous acetylcholine in sustaining bronchoconstriction, illustrating the mechanisms by which inflammation worsens the FEV1 response to the MCh challenge

Impact:

The Respiratory PhysioPD Platform research provided a prospective evaluation of bronchoconstriction outcomes for therapies that interact with pulmonary muscarinic biology to help guide rational drug development

Oncology

Market Model

Challenge:

The client wanted to know how their new screening test in development for a specific cancer type could compete with established and potential new test options as well as to identify which test attributes are most important to prescribers

Approach:

We conducted a Rosa Market Model study with physicians (PCPs and Specialists) to determine expected uptake of the new test given various assumptions about their test’s performance on attributes such as accuracy, logistics, recommendations and patient cost

Results:

Physician preference data indicated that the new test could compete with established options as well as potential new tests and identified which product attributes were most important to those who order these screening tests

Impact:

The test manufacturer can now demonstrate the expected uptake of the new test to potential investors and can focus on improvements to their test’s performance on the attributes that are most important to physicians

Oncology

Phase I

Challenge:

The client requested identification of an optimal dose and dosing schedule for a novel oncology antibody therapy with multiple mechanisms

Approach:

An Oncology PhysioPD Platform was used to identify sensitive metabolic pathways in a growth factor-expressing tumor. The impact of dose and schedule variations on sensitive pathways was evaluated using simulated treatment with the antibody therapeutic

Results:

PhysioPD Research identified key drivers of therapeutic response and found patient characteristics (effector : target cell ratio) had greater impact than variations in drug dose and schedule

Impact:

The PhysioPD Research results increased confidence in the clinical trial design and identified potential biomarkers to guide patient inclusion criteria

Dermatology

Phase I

Challenge:

The client wanted to assess the therapeutic potential of novel oral drugs and anti-cytokine antibodies for psoriasis, and identify the mechanistic drivers and the impact of patient variability on their efficacy.

Approach:

A Psoriasis PhysioPD Platform was developed and qualified using published histology and clinical data for standard of care therapies. Sensitivity analyses were conducted to identify pathways and PK characteristics critical for efficacy. Alternative disease phenotypes were simulated to delineate best- and worst-case scenarios and to show the impact of variability in target-related pathways.

Results:

The Platform identified conditions for which the new drugs are superior to standard of care therapies. Key uncertainties related to target expression and drug biodistribution in the skin were found. Follow-up experiments critical to reduce risk throughout drug development were defined.

Impact:

The Platform showed that decreasing the Phase I clinical trial from 12 weeks to 4 weeks would still demonstrate efficacy for the new therapies, while significantly decreasing the trial costs.

Dermatology

Phase I

Challenge:

Lack of relevant mouse models made it difficult to assess the clinical efficacy of a novel antibody and compare it to an approved treatment for moderate-to-severe Atopic Dermatitis (AD).

Approach:

Build an AD PhysioPD Research Platform representing the AD pathophysiology and using a virtual population with mechanistic variability impacting the clinical response to evaluate the efficacy of the novel antibody across multiple dosing schedules.

Results:

Simulations show stronger and faster improvement in the EASI clinical score in the majority of AD patients compared to the currently approved treatment.

Impact:

The novel antibody was prioritized for a Phase I clinical trial in healthy volunteers and AD patients

Neurology

Phase II

Challenge:

The client wanted to know what dose and dosing strategies would be optimal in reducing side effects of hormone-deprivation therapy in patients treated for breast or prostate cancer

Approach:

Rosa created a quantitative systems pharmacology (QSP) model to evaluate the effect of the compound administrated with specific hormone-deprivation therapies and simulated treatment effects in female and male Virtual Patients

Results:

Simulations showed that administration of the compound reduced the side effects in both male and female patients treated with hormone-deprivation therapy

Impact:

Simulations increased confidence in the compound and provided actionable information on dose amount, dosing strategies, and follow-on research

Immuno-Oncology

Phase II

Challenge:

To identify patient characteristics indicative of therapy responders/non-responders, a client required evaluation of the efficacy and dosing strategies of an interleukin-2 receptor subunit beta (CD122)–biased agonist as a monotherapy and in combination with a programmed cell death protein 1 (PD-1) inhibitor

Approach:

An Immuno-Oncology PhysioPD™ Research Platform and Virtual Patients (VPs) with mechanistic variability that would impact the clinical response to various therapies were used to assess the efficacy of therapies on clinical outcomes.

Results:

PhysioPD Research suggested the CD122 agonist combined with a PD-1 inhibitor showed superior efficacy compared with PD-1 inhibitor monotherapy in PD-1 inhibitor non-responder VPs. Simultaneous dosing of the CD122 agonist and a PD-1 inhibitor may be more efficacious than sequential alternate dosing or preloading with either drug

Impact:

The PhysioPD Platform Research provided a mechanistic-based identification of which patients would have the best response to treatment and support for a drug combination therapy

Cardiovascular Disease

Phase II

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

Alzheimer's disease

Phase III

Challenge:

The client wanted to integrate known plasma, CSF, and brain data into a mechanistic representation of amyloid and tau progression and assess the short and long-term impact of different therapeutic monoclonal antibodies on amyloid beta and tau in Alzheimer’s disease.

Approach:

An Alzheimer’s Disease PhysioPD Platform was developed to represent Aβ and tau disease progression and treatment mechanisms.

Results:

The Alzheimer’s Disease PhysioPD Platform reproduced untreated AD progression and published and proprietary treatment effects in a range of AD patient phenotypes.

Impact:

The client used the Platform to anticipate outcomes of other therapeutic approaches, interpret novel biomarker data, and investigate the impact of genetic variants on progression and treatment.

Type 2 Diabetes

Phase III

Challenge:

An FDA review found a perceived inconsistency between reductions in glycated hemoglobin (A1C) and average plasma glucose changes in a clinical trial of a drug with a poorly characterized mechanism of action. A client requested an evaluation of the data and identification of potential reasons for the perceived inconsistency

Approach:

Research utilized a Type 2 Diabetes (T2D) PhysioPD™ Research Platform with Virtual Patients (VPs) consistent with client Phase III trial data to generate hypotheses explaining the observed relationships between A1C and glucose.

Results:

PhysioPD Research found that the selection of clinical trial subjects and sampling times of fasting plasma glucose likely contributed to the perceived mismatch between A1C and glucose. The variability in dietary carbohydrate between clinical trial sites may have impacted the observed response

Impact:

The results of the PhysioPD Research informed the client strategy for planned FDA discussions, and resulted in recommended strategies for future T2D drug trial design

Oncology

Phase IV+

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.

Neurology

Phase IV+

Challenge:

Clinical trials of drugs like naloxone, that reverse opioid overdoses are not ethical, yet the current approved dose is often insufficient to reverse overdoses of synthetic opioids such as fentanyl, which are faster-acting and more potent than heroin.

Approach:

The FDA recommended receptor modeling as a way forward so together with the client we developed a QSP model with competitive binding of opioids and naloxone.

Results:

Simulations using the Opioid PhysioPD™ Platform demonstrate significant added benefit of higher naloxone doses in displacing fentanyl from the mu receptor.

Impact:

The client is using the simulation results in lieu of clinical trials to support discussions with regulators.

Urea Cycle Disorder

Phase IV+

Challenge:

Client wanted to evaluate the advantages of administering their drug in the fasting state for treating urea cycle disorders (UCD)

Approach:

Rosa adapted a previously published UCD model for BUPHENYL and RAVICTI to include the client's drug pharmacokinetics

Results:

We showed that fasting administration of the drug provided more active drug than the same dose administered fed, thus providing more ammonia removal. A potential competitive advantage over competing drugs.

Impact:

The dose and safety recommendations were provided to the FDA as part of an expanded access filing.

Orphan Disease

Market Model

Challenge:

The client wanted to know how their new drug for an orphan disease which had just completed a Phase 3 clinical trial would be used by two physician specialties for adult and pediatric patients with the condition.

Approach:

We conducted a Rosa Market Model study with the two physician specialties who treat these patients to determine expected uptake of the new drug given various assumptions about efficacy data, safety data, dosing and insurance coverage.

Results:

Physician preference data indicated the potential use of the drug for the intended populations by both physician types given assumptions about the attributes of the agent.

Impact:

The drug manufacturer was able to use the findings of the study to inform the commercialization strategy and the launch of the drug.

Diagnostic Test

Market Model

Challenge:

The client wanted to know how their new diagnostic testing system in development for hospital laboratories could compete with established and potential new systems as well as to identify which system attributes are most important to physicians and hospital labs.

Approach:

We conducted a Rosa Market Model study with hospital based physician specialists and hospital lab directors to determine expected uptake of the new diagnostic testing system given various assumptions about their system’s performance on attributes such as accuracy, logistics, turnaround time and cost.

Results:

Preference data indicated what the new test would need to offer in terms of performance on key attributes to be able to compete with established options as well as potential new diagnostic testing systems.

Impact:

The diagnostic testing system manufacturer continued development of their system now knowing which attributes are most important to Physician Specialists and Hospital Lab Directors and what levels of performance their system needs to achieve on these attributes to be competitive with current and future options.