Companies have reversed the decline in the returns from pharma R&D
Predicting the future of healthcare and life sciences in 2025
Welcome to the seventh in our series of Life Sciences and Healthcare predictions 2025.
Prediction for 2025. Pharma R&D processes use AI-enabled digital platforms, FAIR (Findability, Accessibility, Interoperability, and Reuse) data principles and research partnerships with academia and AI for drug discovery and digital tech companies. This has improved success rates and reduced the time and cost of drug discovery. At the same time, innovative clinical trials (using digital technologies, AI and RWE) have defined new patient-centric digital endpoints and refined indications. Pharma companies employ data-rich visualisation tools to operate virtual clinical trials: enabling faster recruitment/enrolment/monitoring of more diverse patient groups. Apps, wearables, eConsent platforms and telehealth all reduce the time commitment and financial costs of bringing drugs to market.
The world in 2025
- AI identifies novel compounds. The number of novel compounds identified using AI has increased alongside better knowledge on disease mechanisms, as a result a greater proportion of R&D pipelines comprise of drugs for more precise pathologies
- Early-stage research. De novo design and/or in silico computer simulations are used to quicken decision making at key milestones.
- AI-enabled clinical trial innovation. Digital twins, advanced analytics and control towers simulate and monitor trial costs, improve patient enrolment and retention and the likelihood of success. Patient groups with a unique 360-degree perspective on patients’ lives provide regular input to the design and management of clinical trials.
Conquered constraints in 2025
- Skills and talent. R&D scientists are increasingly a blend of clinician, natural scientist and computer data scientist. Companies partner with academia/AI for drug discovery companies and tech giants to bring people with proficiency in data science/data ethics into R&D. Leaders with AI-friendly, tech-savvy boards create new businesses/operating models.
- Funding. Biopharma companies have invested in data, analytics, technology and research collaborations. Faster drug discovery, use of synthetic control arms and improved patient clinical-trial recruitment/retention reduces R&D costs, reverses the decline in ROI and attracts investment.
- Regulation. A new regulatory paradigm means regulators accept RWE in support of new drug applications/label expansions/revisions. They’ve also increased flexibility, transparency, speed of approval and collaborate globally to establish new evidence frameworks.
- Data and interoperability. HIPAA and GDPR compliant cloud, quantum computing and AI-enabled services/tools facilitate global FAIR data management and sharing. Blockchain technology is also used to verify the origin/veracity of dossier submissions.
A snapshot of how the regulatory function of a biopharma company operates in 2025
Luis is the regulatory affairs director of MJ Biopharma and is accountable to the Board.
He has not only automated the company’s dossier compilation to reduce the time/cost of the marketing authorisation applications process, but uses AI to identify anomalies in dossier compilation.
Automation is used across the clinical development process to improve regulatory compliance. While the custody and serialisation of blockchain capabilities enable real-time tracking of the control, transfer and distribution of medicines to trial participants.
Luis has transformed pre-authorisation information management by leveraging AI and BI capabilities (based on his understanding of the regulators own use of advanced analytics to detect patterns and trends) to demonstrate the products’ safety and efficacy.
Evidence in 2020
- Trials.ai’s clever use of its proprietary database. Trials.ai uses AI to analyse sets of data (e.g. clinical studies, medical journals, regulatory guidance) to improve study design. Using their proprietary codified database, they unlock info, derive insights and make recommendations to trial sponsors to design/optimise trial protocols: saving money and time. For one client, Trials.ai reduced study timelines by 33% and data errors by 20%.
- Exscientia originator of the first AI-designed molecule to enter clinical trials. It has developed a full-stack AI-driven drug discovery platform from target identification to drug design and optimisation of novel drug candidates. Five assets have been delivered in under 14 months (compared to the 5-year industry benchmark), with drug discovery cost savings of more than 80 per cent (30 per cent achieved for the entire drug development process).
How COVID-19 has accelerated this prediction
Deloitte’s view
In response to the pandemic, the pharma industry, academia, biotech and governments initiated scientific ventures funded by governments, multilateral agencies, not-for-profit institutions and the private sector.
Trade secrets and intellectual property were widely shared to expedite the search for new treatments/vaccines, with regulators quickly entering into discussion aimed at supporting the most promising innovations.
As of November, 10 vaccine candidates were in Phase III trials, faster than any other vaccine in history, and three hope to gain rapid approval by the end of 2020. Reassuringly, the CEOs of nine leading developers signed a pledge committing to uphold the integrity of the scientific process and provide robust evidence of safety and effectiveness so that vaccines can provide some insurance against continued health societal and economic impacts of the pandemic.
From genetic testing to discovery to drug development
23andMe, a genetic-testing company, researches the genetic basis of disease, leveraging genetic data to develop new treatments. During the pandemic, their research platform identified a number of genetic/non-genetic associations for susceptibility/severity to COVID-19. In less than four months, more than one million 23andMe customers took part in the research (15,000+ tested positive for COVID-19 and 1,100 required hospitalisation).
Explore more
Our series of ten predictions for the life sciences and healthcare industry looks ahead to the year 2025 to help you see what’s coming and to keep your organisation moving forward.
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