Drug Discovery In A Post-Pandemic Era
How Data Interoperability Will Accelerate Innovations
and Empower Patient-Centric Care
Shreejit Nair
SVP - Life Sciences, CitiusTech
June 23
Article
Insights
The value of massive, integrated data platforms comprising genomics and omics data in drug discovery is significant: modest estimates suggest that such platforms will generate $25bn in value annually over 20+ years.
- Data quality and verifiability are crucial to ensure trust and precision in the outcome of clinical trials. Today, data collection and capture mechanisms are largely fragmented, and manual data management can introduce errors and time overheads.
- Data interoperability eliminates data management overheads and builds trust and provenance while building a synergistic perspective with all data sources and streams. This will speed up the outcome of clinical trials while reducing the costs associated with clinical data management.
From sampling techniques and bio analytics to trial design and regulatory compliance, the COVID-19 pandemic left no aspect of drug discovery and rollout untouched. In the process, data interoperability has redefined the horizons of drug discovery.
The pandemic was a defining moment in transforming the global healthcare ecosystem. Laboratories, pharma companies, healthcare providers, and regulators had to rethink their long-established operating models within days. In this process, digital technologies emerged as a critical enabler of the urgently needed shift. Healthcare IT transformation evolved by a decade, and patients quickly readjusted to the new dynamics. This evolution has, without a doubt, redefined critical aspects of drug discovery.
Will these trends stick beyond the pandemic now that things are back to normal?
The successful development of a vaccine months after a global spread unveiled the possibility of shrinking the drug development life cycle by tenfold and the potential for cross-functional, cross-organizational collaboration in care delivery.
Key Challenges and Shortcomings
Drug discovery is a complex process that rests on breakthroughs in scientific knowledge, well-calibrated trial designs, and collaborative efforts across multiple stakeholders. The average drug development lifecycle spans 10-15 years. The pandemic left none of these aspects untouched. Clinical trial sites had to shut down, the collaboration had to move to digital channels, and labs were suddenly out of access. This rendered the legacy pharma operating models unviable, and industry leaders had to reimagine every workflow from the ground up.
At the same time, the pandemic also gave way to unprecedented paradigms and dynamics. For instance, global and national dashboards were implemented to monitor disease spread, telehealth, and medical device adoption granularly soared, and collaboration amongst governments, drug companies, academics, and healthcare providers enabled the development of new perspectives.
Each of these aspects also highlighted some critical shortcomings within the system. For example, large, integrated datasets (comprising raw medical data, EHRs, and clinical trial results) emerged as necessary to support global research efforts. However, these efforts were challenged due to disparities in the formats of captured data, clinical codes, lab results, numerical outputs, and standards that various organizations followed. In other words, data interoperability surfaced as a critical driver for supporting COVID-19 interventions.
Innovation in Drug Discovery Instigated by the Pandemic
In response to the above challenges, the pharma industry led a blitz transformation, which paved the way for novel drug discovery and development approaches. The successful development of a vaccine months after a global spread unveiled the possibility of shrinking the drug development life cycle by tenfold and the potential for cross-functional, cross-organizational collaboration in care delivery.
Incremental Steps Towards Healthcare Data Interoprability
The value of massive, integrated data platforms comprising genomics and omics data in drug discovery is significant: modest estimates suggest that such platforms will generate $25bn in value annually over 20+ years. Such data platforms can help develop insights into disease progression and pathways and build precise therapies. However, data interoperability is a crucial barrier to realizing this vision.
During the pandemic, positive steps were taken in this direction. Collaborative data infrastructures were operationalized by various bodies (4CE, CORD-19, and EU Open Data Portal are leading examples), and HL7 FHIR was used to define virus data elements. Some healthcare organizations also built data-sharing applications based on the FHIR standard.
Lastly, regulatory efforts also are bringing data interoperability to the forefront of healthcare transformation. 21st Century Cures Act, which enables investments in data strategies and real-world evidence, is a crucial example.
Data Interoperability in Healthcare: What Comes Next?
Clinical trials have already used Electronic Data Capture systems for over two decades. Moving ahead, more and more data sources will inform drug discovery processes: including, but not limited to, clinical trial management systems, EHRs, ePROs, social media streams, and results and datasets from other clinical trials and healthcare bodies. Collecting, cleaning, and organizing data from these sources requires significant manual effort, which will be primarily eliminated with better data interoperability.
An API-based data architecture, data adaptors, and data transformation and harmonization platforms will be crucial in building cross-system interoperability for these data sources. In addition, patient consent procedures must be built into such efforts to enable trust and implement provenance into the validity of the data. The technologies to support such a vision are already mature and in the market.
Toward Patient-Centric Clinical Trial Design
During the pandemic, several pharma companies restarted existing trials and piloted new ones with decentralized models. Changes in sampling, bioanalytical techniques, and lab operations accompanied this shift from clinic-centric to patient-centric trials. Decentralized trials also emerged as more convenient and accessible alternatives for patients. In decentralized trials, the lack of access to patients triggered the shift from phlebotomy to micro sampling, driven by mobile nursing devices. This also required developing and validating new assays to verify the accuracy of the recorded data and inferred pharmacokinetic observations.
Decentralized trials also required e-consent capabilities and simple, intuitive interfaces connecting patients to clinical trialists. Moreover, new participant engagement methodologies were piloted, and direct-to-patient logistics were engaged.
Data quality and verifiability are crucial to ensure trust and precision in the outcome of clinical trials. Today, data collection and capture mechanisms are largely fragmented, and manual data management can introduce errors and time overheads.
Decentralized Trails: Data Interoperability is the Key
Data quality and verifiability are crucial to ensure trust and precision in the outcome of clinical trials. Today, data collection and capture mechanisms are largely fragmented, and manual data management can introduce errors and time overheads.
Data interoperability eliminates data management overheads and builds trust and provenance while building a synergistic perspective with all data sources and streams. This will speed up the outcome of clinical trials while reducing the costs associated with clinical data management.
Moving Ahead
The pandemic has stirred the healthcare ecosystem to leverage healthcare data interoperability in novel ways. It has provided a much-needed impetus for widespread adoption. This will enable more repeatable breakthroughs with evidence-based, AI-driven approaches in pharmaceutical R&D and empower patient-centric trial designs.
With this shift, the patient is now at the heart of drug discovery and development. While the industry may still be a few years away from personalized drug development, sub-year drug development lifecycle and evidence-based drug discovery are now within reach.
References:
- https://pharmanewsintel.com/news/understanding-the-drug-development-life-cycle-its-role-in-pharma
- https://www.mckinsey.com/industries/healthcare/our-insights/telehealth-a-quarter-trillion-dollar-post-covid-19-reality
- https://www.mckinsey.com/industries/life-sciences/our-insights/better-data-for-better-therapies-the-case-for-building-health-data-platforms
- https://academic.oup.com/bib/article/22/2/812/6103007#232142161
- https://blog.hl7.org/hl7_fhir_applications_beging_to_support_better_response_to_covid-19
- https://academic.oup.com/clinchem/article/67/4/592/6105075