A virtual Design Lab held on June 10 and 11 highlighted progress made in moving from design to application of key elements of a LEAPS learning system within our safe haven testbed environment. Expanding from our Rheumatoid Arthritis (RA) pilots, we are testing our RWE regimen optimization design principles in other therapeutic areas from COVID to depression to lipid management and cancer tumor profiling. This event provided important input from our collaborator community on the consolidation of our next steps into two central pillars of innovation for application to RA and other diseases, described below.
1. Predictive Outcomes Platform
LEAPS has engaged with MIT’s Lincoln Labs to aid the DOD’s Defense Threat Reduction Agency (DTRA) address medical and force planning challenges associated with the COVID PASC (Post-Acute Sequelae of SARS-COV-2). This sub-population of “long haulers” was selected as an initial use case for rapidly developing an ongoing medical countermeasures capability for emerging biothreats. A Predictive Outcomes Platform, inspired by our work to date in the LEAPS Real World Discovery Platform (RWDP), was conceptualized to address the need to quickly identify, predict, and optimize real-world drug therapy treatment regimens in rapidly evolving and highly uncertain conditions. The Platform will enable clinically meaningful hypothesis generation and validation at scale using diverse, distributed real-world data sources, including Patient Generated Health Data.
This pandemic provides a particularly timely and compelling need for generating high-quality, actionable RWE in the face of imperfect and fragmented data, where dynamic uncertainties about both the disease and its treatment threaten lives, public health, and national security. This platform-based capability to generate predictive models that improve clinical and functional outcomes is now ready for prototyping.
Current Engagement Opportunity:
Integrating Evidence Workstream: Core to the design of the Predictive Outcomes Platform is that patient-level data is not shared. Rather, evidence that is generated behind the firewalls of participating organizations is shared with a central coordinating organization that serves as a neutral intermediary that integrates the disparate elements of evidence using meta-analytic methods. A team focused on elucidating and demonstrating key methodologic elements of this approach is now being formed and welcomes new members. If you are interested in learning more please contact Keileen (khopps@mit.edu) to receive a more detailed abstract of this opportunity when it is available.
2. Adaptive Reimbursement Pilots to Incentivize Improved Outcomes & Critical Learning
The adoption of high-quality evidence into clinical decision-making is notoriously slow in healthcare. At the same time, there remain many critical knowledge gaps for which evidence is currently not being developed due to the lack of effective incentives.
Adaptive reimbursement addresses both issues by harnessing the entire downstream incentive system (from performance-based contracting to patient benefit designs to utilization management) to impel use of existing evidence in clinical care and leverage the outcomes data to generate new clinically actionable evidence.
Through LEAPS multi-stakeholder collaboration processes, pilot projects are advancing in Cardiovascular (Lipid Management) and Oncology (use of Next Generation Sequencing tumor panels). Some areas, such as use of pharmacogenomics for depression therapy did not appear as immediately promising for rapid implementation and so were placed on hold with an expectation to revisit in the future. These discussions also inspired the additional nomination of another potential opportunity (now being vetted) in Cardiovascular focused on the use of coronary computed tomography angiography (CTA) as a first line diagnostic test for stable chest pain.
Current Engagement Opportunities:
Each pilot concept team (Lipid Management and Oncology/NGS) would welcome new members. LEAPS also continues to seek additional Adaptive Reimbursement pilot concepts for consideration. If you are interested in participating, please contact Keileen (khopps@mit.edu) for further information.