Market Access
Market Access / HEOR & Pricing
Unveil the full medical value of your assets.
You have successfully demonstrated the safety and efficacy of your drug with a positive Phase III trial. Aiming for regulatory approval, access and pricing negotiations, your focus now turns to ensuring your drug performs just as well in real-world settings as it did in clinical trials.
How to make sure safety, efficacy and effectiveness outcomes will be confirmed on a wider diversity of patients, while demonstrating additional value compared to the standard of care? How to provide HTA agencies and payers with reliable prospective evidence of the medico-economic benefits to be generated by your drug, solely based on clinical trial results?
Our validated and transparent patient-level models and simulators accounting for disease and care diversity and evolution will help you take up these challenges.
Traditional approach :
• Traditional medico-economic models do not account for disease and care heterogeneity.
• High uncertainty due to disease heterogeneity slow-down access and pricing negotiations.
• Recruitment difficulties
• Suboptimal post-approval study designs.
Opportunity for improvement : Patient-level simulations accounting for disease and care diversity and evolution.
• Reliable medico-economic projections capturing high costs and high unmet needs patients.
• Optimal positioning in treatment sequence versus standard of care.
• Early adequation between price and long-term outcomes / Optimal value-based contracting.
• Optimal post-approval study designs.
our use-cases
Predicting effectiveness from efficacy for an asthma drug to ascertain medical value towards regulators and payers
Important unmet needs remain in the treatment of asthma. Characterizing drivers of effectiveness and building a predictive disease model of asthma aapplicable to the real-world condition of drugs use allowed for predicting the effectiveness of a new anti-asthma drug from trial efficacy, ascertaining its safety and value for regulators and payers. This model led to de-risking phase 3b pragmatic trials and to the conduct of the first pragmatic pivotal trial within healthcare electronic databases.
Predicting long-term outcomes from short-term endpoints to demonstrate drug value in rare disease
Associations between, disease symptoms and payer-relevant outcomes can be difficult to establish for rare or chronic diseases. Predicting long-term outcomes from short-term endpoints allows to demonstrate drug value. The predictive potential of disease-related characteristics can be assessed through a disease model to predict long-term survival from functional outcomes. This helped to demonstrate that sIBM patients have higher risks of premature death.
Modeling care and disease progression to optimize switching time in heart failure
New Heart Failure drug showed superiority to Standard of Care drugs in trials. Yet poor average relative effectiveness was observed in real-world observational studies, hence the need to demonstrate when and for whom to switch to maximize medical value. This method allows to predict effectiveness in Real World simulating Real World outcomes. Modeling and simulation allowed for comparing treatments sequences to optimize switching strategies. Early switch was shown to maximize medical value and care efficiency.
Modeling care and disease progression to optimize switching time in heart failure
New Heart Failure drug showed superiority to Standard of Care drugs in trials. Yet poor average relative effectiveness was observed in real-world observational studies, hence the need to demonstrate when and for whom to switch to maximize medical value. This method allows to predict effectiveness in Real World simulating Real World outcomes. Modeling and simulation allowed for comparing treatments sequences to optimize switching strategies. Early switch was shown to maximize medical value and care efficiency.