Diane Lacroix, Vice President – Clinical Data Management, eClinical Solutions
Personalized medicine carries immense potential for improved patient care in creating highly tailored therapies that are unique to an individual's genetics and need, increasing accuracy while reducing harm. This precision approach could unlock better understanding of disease; help identify patient populations for smaller, faster trials; and even predict or prevent disease. As developments in personalized medicine progress, realizing these outcomes open possibilities for enhanced engagement and trust with patients, helping achieve patient-centered research and care. Getting there depends on data — a lot of it — and holistic data insights. Personalized medicine relies on vast data sets from a variety of sources and systems, including omics data, labs and images, and data from wearables, sensors, and apps — along with traditional sources like electronic data capture (EDC) and electronic health records (EHR). To piece together a complete picture and drive decisions, these data must be integrated and interrogated for insights. Science and technology have advanced the potential for personalized medicine, but they've also increased the data complexity of modern clinical trials and contributed to fragmentation and silos. Operational challenges in data processing must be addressed in this data environment. Realizing the opportunity at hand requires addressing the data challenges of modern research. Robust data infrastructures need to enable interoperability, automation, artificial intelligence (AI) and machine learning (ML) — alongside processes adapted accordingly — so that teams can bring together and analyze these continuous streams of diverse data for the intelligence that drives personalized medicine, efficiently and at scale.
Nerissa Kreher, M.D., Chief Medical Officer, Alltrna
Personalized medicines are essential for treating certain diseases, but the current approach of developing one drug for each of the 6,000+ rare genetic diseases is not feasible.
By rethinking disease classification not based only on clinical symptoms or phenotype (e.g., hemophilia B or muscular dystrophy) but by shared genetic alteration, like a premature termination codon (PTC), we can develop drugs differently – ones that are personalized to a patient’s specific mutation but also applicable across many diseases.
Mutations that cause PTCs turn an mRNA codon that would normally encode for an amino acid, into a stop codon. The result: the full-length protein is not made and either the protein is completely missing or a toxic one is created. A single, engineered, tRNA molecule could recognize this PTC and place the correct amino acid — thus restoring the functional protein production.
PTCs cause genetic disease in ~10% of patients (~30 million). At Alltrna, we leverage tRNA biology to develop medicines for people with stop codon disease. As many diseases share the same PTC, we are exploring basket trials to accelerate the rare disease drug development process with a personalized tRNA medicine that carries the potential to unify treatment for millions of patients.
Fran Brown, Ph.D., Senior Vice President, Drug Development Science, Certara
More than ever before, "personalized medicine" can improve patient care. New medicines are approved based on data acquired in a subset of the target patient population. This excludes many subgroups, such as pregnant or lactating women, in which the benefit–risk is assumed to be that of the general population. Such subgroups may be less likely to experience treatment benefits or more likely to experience adverse effects or require a different dose for optimal therapy.
Rapid advances in genomics, proteomics, and metabolomics combined with ML and AI can leverage these vast data sets and rapidly identify differences across the population. However, assessing the clinical relevance of such differences and how to manage those at a patient level remains challenging.
Regulators are increasingly accepting biosimulation tools to bridge these gaps. These tools range from models developed during product development to understand the relationship between exposure, efficacy, and safety, which are used to identify important patient factors that impact benefit–risk, to those which simulate outcomes in unstudied populations. Biosimulation will become a key enabler of personalized medicine. The next challenge will be creating tools to translate this knowledge into clinical decision-making and which are available at Point of Care.
Daria Donati, Ph.D., Chief Science Officer, Genomic Medicine, Cytiva
For genomic medicine to become part of everyday treatment and life, we need to adjust how we make these therapies. The good news is that, within the space of personalized medicine, there’s a variety of emerging technologies. However, they exist within silos, restricting them to specific areas. One of the biggest challenges, as a company and as a broader industry, will be gathering these diverse technologies and generating synergies between them to generate impactful change. Doing so would provide a unique opportunity to accelerate innovation within the genomic medicine space. If we can foster synergies between already available technologies, we can increase efficiency of manufacturing, reduce the cost of manufacturing, and simplify the process of bringing personalized medicines to the patient, with the potential impact of increasing accessibility.
Nathan Givoni, Chief Executive Officer and Co-Founder, Gelteq
The shift toward personalized medicine is a game-changer for patient care. At its core, it’s about moving from a one-size-fits-all approach to tailored treatments that reflect the individual’s unique biology. As we advance in genomics, AI, data analytics, and manufacturing processes, this approach will redefine outcomes, offering more precision and fewer side effects. However, challenges like data integration, high costs, and regulatory complexity persist, which limit its wide-reaching adoption. These are exactly the kinds of obstacles that fuel our passion for innovation. At Gelteq, we continue to strive to be at the forefront of innovation and ensure our unique gel technology is part of any evolution in medicine. By refining our processes and formulations, we continue to work toward solutions that offer an affordable way to deliver an effective solution, supporting patient well-being and healthcare efficiency. Personalized medicine isn’t just a trend — it will become mainstream, and we are striving to ensure Gelteq is part of that evolution.
Kathy Davy, President of Clinical Next-Generation Sequencing, Thermo Fisher Scientific
Advances in personalized medicine, particularly through next-generation sequencing (NGS) companion diagnostics, are revolutionizing patient care by enabling more tailored treatment approaches, early and accurate diagnosis, and targeted drug development. With a deeper understanding of how genomic variants inform treatment response and outcomes, NGS holds the ability to match patients with more effective and targeted therapies that often have fewer side effects for patients. Additionally, with fast turnaround times, NGS can help ensure that optimal treatments are started as soon as possible, helping patients receive the most effective care throughout their treatment journey.
While therapeutic progress advances, practical challenges can hinder the full benefit of personalized care. Barriers like data integration complexities and inequitable access to advanced diagnostics limit the widespread adoption of personalized medicine. These issues often restrict patient access to lifesaving treatments, particularly in underserved communities. The path forward requires a collective effort to address these challenges through:
Innovative technologies that streamline data analysis and accelerate actionable insights,
Collaborative partnerships across healthcare, research, and technology sectors to improve access, and
Educational initiatives that empower clinical teams to implement precision medicine effectively.
By focusing on these areas, we can drive the global adoption of personalized medicine, ensuring that more patients benefit from the breakthroughs in oncology and beyond.
John Tomtishen, Senior Vice President and General Manager (IDMO Business), Cellares
Over the past decade, we have seen personalized medicine play a critical role in defining the future of patient care. This has been most acutely seen in the use of autologous cell therapies for the treatment of several hematological malignancies, including leukemia, lymphoma, and multiple myeloma. Patients who were on the brink of death have now been cured of their disease. There have also been several promising advancements recently in the use of these therapeutics in earlier lines of treatment in addition to their use in solid tumors and autoimmune diseases.
However, challenges still exist today that are limiting patient access to these therapeutics. Specifically, manufacturing capacity has been outpaced by patient demand due to the complexity associated with the manufacture of “living drugs.” Significant strides have been made though to address these manufacturing bottlenecks through the development of integrated, advanced manufacturing technologies and workflows. These innovations are poised to transform the manufacturing paradigms used to manufacture these therapeutics and reshape patient care through the broader adoption of personalized medicine. Patients will no longer pass away on waitlists due to manufacturing capacity constraints when safe and efficacious therapeutics are readily available.
Richard Chen, M.D., Chief Medical Officer and Executive Vice President of R&D, Personalis, Inc.
When we consider the biotech industry in 2025, we see a strong emphasis on monitoring cancer using blood-based testing and using that insight to guide care. Minimal residual disease (MRD) cancer testing is becoming an increasingly essential part of patient management, as studies show it benefits patients. It enables medical teams to make earlier and more informed decisions in the recovery stages. This shift from reactive to proactive care reduces guesswork and helps provide better peace of mind for patients worried about their cancer returning.
We believe biopharma firms and diagnostic companies will partner more often to increase their respective value opportunities, integrating testing solutions and data analytics directly into trial designs. This can offer a more complete picture of how patients respond, guide clinical strategies, help refine the selection of promising therapeutic approaches, and provide more patient choices. Such integrations may also simplify complex supply chains and create smoother pathways for bringing advanced diagnostics and targeted treatments to patients.
Though challenges remain surrounding seamless technology integration, data interoperability, and equitable access to advanced diagnostics and therapies, addressing these barriers will be critical to realizing personalized medicine's full potential and ensuring its benefits to diverse patient populations.
