Are you about to embark on a journey to update slides and spreadsheets or a journey to shape how patients may experience future benefits?
Imagine a future where you, as a patient can interact with a healthcare provider and receive access to diagnostics with ease and without undue delay, where your diagnosed conditions are then discussed with you, placing you in control of your treatment choices and where information from high-quality clinical trials as well as good quality real-world evidence is presented to you and compared to your phenotypic or genotypic profile, enabling you and your healthcare provider to make an informed choice about your treatment pathways, goals and future. A decision that enables you to clearly see how well the evidence for any diagnostic or treatment matches your individual situation.
This isn’t science fiction, it’s the emerging reality of personalised healthcare that our Integrated Evidence Generation Plans (IEGPs) must evolve to support.
IEGPs have come a long way since they appeared in the industry 15 or so years ago.
Although the infographic above doesn’t cover every situation where IEGPs or equivalent were introduced, IEGPs have evolved over the past 15 years into indispensable tools for coordinating evidence generation across product lifecycles. Initiatives like the IRA and jHTA have pushed “in-market” decision-making to earlier phases, challenging the old phase-by-phase approach, especially in areas like oncology. This will affect all therapeutic areas eventually.
Patient-Centricity as the primary focus
Patient-centricity may mean a move to individuals identifying themselves not as “patients” but as “people with X disease state.” This cultural shift is already underway, with IEGPs expanding beyond regulatory requirements to address all stakeholders—payers, other health and care providers, patients, caregivers, and employers.
The Personalisation Revolution
Monstrous advances in -omics and health data analytics are enabling increasingly individualised treatment options based on phenotypic and genotypic profiles/archetypes for certain diseases.
Of course, for acceleration of such changes to take place more universally, wholescale infrastructure, legal, ethical, collaboration and other challenges need addressing, but we are already seeing such challenges addressed on a manageable scale with unprecedented health data sharing as well as the use of federated datasets leading to better understanding of disease progression characteristics. For patients to share their data in this fashion, legislation also need to change so patients can receive more information from different sources to enable more empowerment over decision regarding their disease trajectory across countries.
Transforming IEG Planning
What does this all mean for IEG planning? A lot! The question isn’t whether personalised healthcare is coming, it’s whether we’re ready to plan for it now and can be at the forefront of this change. Can we envision the future needs of individuals managing their conditions and begin building evidence generation strategies to support more personalised healthcare?
The future demands we move beyond unwieldy documents and conventional milestone-dependent studies. Instead, we may need:
- Continuous evidence gathering about health and disease states through collaborative datasets rather than single, milestone dependent short-term studies
- Integration of reliable and validated wearables data and multi-omic profiling
- Digital twin modelling for predictive insights
- AI-powered analysis and decision support
- Evolved evidence generation planning platforms that accommodate these new paradigms
- Simplified governance processes that enable rapid decision making for impact at scale
With an ever increasing availability and willingness to collaborate across borders to collect and share biological, clinical and epidemiological data amongst others, the future of personalised healthcare may not be just for Hollywood futures.
Are we so far from this reality just now? Think of the future patient, or as they may be known, the person who has good control over X disease state and what they may need to achieve individualisation of their therapeutic goals, and can we incorporate IEG planning for that now?
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