Insight by: Jon Warner, Executive Chair of Citizen Health Strategies (CHS)
The healthcare industry is undergoing a digital revolution. Advancements in digital technologies like artificial intelligence (AI), machine learning, cloud computing, and mobile connectivity are transforming how healthcare is delivered and how diseases are treated. Despite what some might say has been a late start, nowhere is this digital transformation more apparent than in the pharmaceutical sector.
Pharma companies have long recognized the potential for digital technologies to improve drug discovery and development processes, enhance clinical trials, and enable more personalized patient care. Over the past decade, major pharmaceutical players have significantly ramped up their digital health investments and partnerships as they seek to leverage emerging technologies to streamline R&D, gain insights from real-world data, and develop new business models centered around patient needs.
This brief article explores how the pharmaceutical industry is applying digital health and AI technologies across the drug development lifecycle from discovery and preclinical research to clinical trials and commercialization. It analyzes the strategic priorities of leading pharma companies and highlights some of the most promising applications that could shape the future of healthcare.
Applying AI to Drug Discovery and Preclinical Research
One of the biggest opportunities for pharma lies in using AI and machine learning to accelerate and optimize the early stages of drug development. Drug discovery is a lengthy, expensive process that often fails to yield viable candidates. By analyzing vast amounts of biological and chemical data, AI has the potential to significantly boost success rates and cut years off development timelines.
Computational methods like deep learning, natural language processing, and generative design are being applied across target identification, lead optimization, and preclinical testing. Companies are training machine learning models on petabytes of data from scientific literature, high-throughput screening experiments, clinical trials, and more to uncover new insights. This helps researchers prioritize the most promising targets and drug candidates for further investigation.
For example, companies like Exscientia use AI to sift through huge chemical libraries to design novel small molecule leads. DeepMind’s AlphaFold technology helped predict the 3D structures of protein targets, a crucial step in drug design. BenevolentAI applies machine learning to identify relationships between genes, proteins, and diseases to discover new therapeutic hypotheses. These types of AI applications could transform preclinical R&D by accelerating the evaluation of potential new medicines.
Streamlining Clinical Trials with Digital Technologies
Clinical trials have long been a major bottleneck in the drug development process due to their complexity, costs, and regulatory requirements. Here too, digital technologies offer opportunities to make trials more efficient. Technologies like electronic health records, wearable devices, mobile apps, and telehealth are generating unprecedented amounts of real-world data that can provide insights into patient populations and disease progression.
Pharma companies are tapping into these new data sources and using AI to optimize trial design, recruitment, monitoring, and analysis. For example, AI algorithms can help match the right patients to the most suitable clinical trials based on their medical records and genomic profiles. Wearables and mobile apps enable remote and decentralized clinical trials, reducing costs and barriers to participation. AI also helps automate tasks like adverse event detection from medical records and image analysis of scans.
Partnerships between pharma and digital health startups are fueling innovation. For instance, companies like Science 37 use virtual and decentralized approaches combined with AI to conduct siteless clinical trials entirely through telehealth. This could make trials more patient-centric and inclusive of populations traditionally underrepresented. As regulatory frameworks evolve to embrace real-world evidence, digital technologies will continue transforming the clinical research landscape.
Personalized Medicines Driven by Genomics and Real-World Data
Advancements in genomics, connected devices, and AI are enabling a shift toward more personalized, precision medicines. Pharma is tapping into the flood of genomic and real-world data to gain a deeper understanding of individual disease risk, progression, and treatment response. This helps identify biomarkers and develop therapies targeted at the molecular level for specific patient subgroups.
For instance, AstraZeneca recently partnered with Anthropic to apply self-supervised learning to real-world datasets spanning millions of patients. This uncovered novel biomarkers and molecular subtypes to inform the development of more personalized oncology medicines. Roche is also using real-world data and AI to develop companion diagnostics that can identify which patients are most likely to respond to certain targeted therapies.
As genomic sequencing becomes cheaper and more ubiquitous, the ability to match drugs to an individual’s unique molecular profile will revolutionize how diseases are treated. AI will play a key role in analyzing the deluge of multi-omic data and real-world evidence to power precision medicine approaches. This has the potential to dramatically improve outcomes while reducing trial-and-error prescribing.
Patient-Centric Digital Platforms and Services
Pharma is also leveraging digital technologies to develop new direct-to-patient business models centered around wellness, prevention, and managing chronic conditions. Companies are building digital platforms that integrate telehealth consultations, online pharmacies, clinical support tools, wearables, and apps to deliver more holistic care.
For instance, Lilly launched Lilly Diabetes Solution Center and Lilly Insulins Valyou Savings Program, which provide virtual coaching, connected devices, and financial assistance tools. Pfizer has rolled out a suite of digital health solutions under the PfizerForAll umbrella focused on areas like cancer care, rare disease, and women’s health. These platforms aim to empower patients, enhance medication adherence, and generate real-world evidence on treatment effectiveness.
By shifting to patient-centric models, pharma can play a more proactive role in managing health beyond just drug supply. AI will be crucial for powering these platforms, helping to personalize interactions, detect health changes, optimize dosing, and predict risks of complications or comorbidities. As healthcare moves increasingly to value-based models, digital health solutions will be a key differentiator for pharma companies.
Digital Health and AI: Transforming Pharma R&D and Beyond
The pharmaceutical industry’s growing investments in digital health reflect a recognition that emerging technologies hold immense potential to revolutionize drug development and healthcare delivery. AI in particular is poised to transform R&D by accelerating target identification, optimizing clinical trials, enabling precision medicine approaches, and generating insights from real-world data at an unprecedented scale.
Digital platforms also allow pharma to shift from a product-centric model to one centered around patient needs, experiences, and well-being. By leveraging technologies like telehealth, connected devices, predictive analytics, and personalized engagement tools, companies can play a more proactive role in managing health beyond just drug supply. This will be crucial for addressing the growing burden of chronic diseases.
While significant technical and regulatory challenges remain, the integration of digital health and AI across the drug development lifecycle and into new direct-to-patient business models holds immense promise to streamline R&D, improve outcomes, and reshape healthcare systems worldwide. As these technologies continue advancing at an exponential pace, their impact on pharma innovation, clinical research, and patient care will only accelerate in the coming years. The digital transformation of healthcare is well underway.
