The MAPPs Ecosystem
See below explanations of each stage of the process.
MAPPs are supported by multiple sources of data. These datasets can be from the Real World such as medical records, as well as mHealth tools such as mobile phones and linked sensors. Data can include sources not traditionally used in clinical decision making like food purchase history to create full picture of patient health and treatment effectiveness. Ideally, all of this robust data is captured and analysed in real time.
As the evidence base expands, health technology assessment and pricing will adapt and evolve. This means it will be theoretically possible for pricing to move both higher or lower depending on observed data, and HTA authorities will re-evaluate their assessments based on the increasing and expanding data package.
As MAPPs pathways launch with a less defined package of evidence, it is critical that tools and methodologies for the evaluation and capture of real world evidence serves to expand the knowledge base. As this knowledge expands, the methodology, population, and trial design will adapt and change to meet the needs demanded by the expanding evidence.
Once a new therapy has been placed into MAPPs, the patient population receiving the therapy may need to be altered based on the evidence collected. This could include the theoretical need to limit populations due to previously unknown side-effects in sub-populations or the wish to expand the number of recipients due to a larger than anticipated group of identified responders.
Given that benefit risk decisions will be made initially with a smaller evidence base, patients will be engaged at the start of the process to ensure that they are well informed regarding the need to make decisions in an environment of greater uncertainty. As more evidence is generated, the initial benefit risk assessment will be updated and informed based on the increase of knowledge by all stakeholders, including patients.
A key point of MAPPs is the multi-stakeholder decision making process before, during, and after launch over the entire lifetime of a therapy. Modeling and simulation of the potential impact on all stakeholders engaged in MAPPs will help inform and enlighten critical decisions that need to be made when placing a new therapy into a MAPPs pathway.’
The knowledge base of MAPPs will evolve over the lifetime of the therapy, as real time and real world evidence is incorporated into the decision making process. As this evidence base evolves, the clinical trial design may adjust and adapt based on the performance of the therapy.
A fully functioning MAPPs ecosystem would see patients receiving needed new therapies in a more timely fashion in a more sustainable health system for all stakeholders.