The Current and Future State of Personalised Medicine

Personalised medicine is transforming healthcare by harnessing molecular genetics, big data, screening, and early diagnosis to deliver targeted treatments. Unlike traditional one-size-fits-all approaches, it tailors therapies to a patient’s unique genetic and biological profile. Beyond treating illness, it enables proactive, preventative care by identifying potential health risks early and bringing awareness to individuals. By integrating collaborative healthcare solutions that ensure the right treatment is delivered to the right patient at the right time, personalised medicine is redefining medical standards. With a well-established connection between high-quality care, patient engagement, and improved health outcomes, this rapidly evolving field presents significant opportunities for both healthcare providers and businesses.

Personalised medicine shifts the role of patients from passive to active, as patients are increasingly engaged in pursuing medical insights and making decisions about their treatments with healthcare professionals rather than simply following a doctor’s orders. The traditional top-down approach in healthcare is transitioning into a more collaborative model, where patients and healthcare providers work as partners. This shift represents a transfer from paternalistic medicine where doctors make decisions on behalf of patients, to participatory medicine where patients play an active role in their treatment plans. There are numerous benefits to personalised medicine including improved diagnostic accuracy, optimised treatment selection, increased patient engagement, reduced side effects, and ultimately, better health outcomes.

Key technology advances driving personalised medicine

The progress of personalised medicine has been advanced by key technologies, including developments in AI, CRISPR-Cas9, mRNA, and biomarkers. These innovations are crucial for achieving cost-effective healthcare solutions and improving overall patient outcomes.

AI has transformed medical data analysis through integrating enormous amounts of patient-specific information to identify mutations, prescribe drugs, and predict responses to treatments. With tools like Tempus and Foundation Medicine using AI to analyse cancer mutations and recommend targeted therapies, and generative AI aiding in drug discovery by designing novel drug candidates, patient diagnoses are becoming more accurate and accelerated. Machine learning is also transforming oncology, with machine learning classifiers like OncoNPC being trained on more than 36,000 tumours to identify cancers of unknown origin and guide treatment strategies. Similarly, AI-driven models like eDICE are revolutionising the field of epigenetics by predicting variations that influence disease risk and treatment response. By leveraging epigenomic data to train algorithms, the model has successfully identified individual epigenetic differences, demonstrating its potential to enhance the role of epigenomics in personalised medicine.

Additionally, AI is being utilised to personalise therapies based on an individual’s microbiome. Researchers have developed a model trained on over 41,000 microbiome-drug interactions, enabling the prediction of drug-induced disruptions to the microbiome and identifying which microbial taxa are most affected. This is an important advancement, as the microbiome plays a crucial role in drug metabolism, influencing both the efficacy of treatments and the likelihood of adverse drug reactions.

CRISPR-Cas9 is a major advancement in personalised medicine, allowing precise modifications to DNA and genetic-level changes. The FDA's recent approval of Casgevy, a CRISPR-based therapy for sickle cell disease, marks a significant milestone in genetic medicine and is projected to achieve global sales of $593 million by 2029. With its ability to silence or modify genes, CRISPR-Cas9 has been employed in one of the most notable applications of personalized cancer therapy, CAR T-cell therapy. This approach involves extracting and genetically modifying a patient’s own T-cells to recognise and eliminate tumours before reinfusing them into the body. It has demonstrated remarkable success in treating leukaemia and lymphoma, offering hope to patients with cancers that relapse after chemotherapy.

Meanwhile, mRNA therapies have made significant strides beyond their success in COVID-19 vaccines, with Pfizer’s Comirnaty being the first mRNA-based COVID-19 vaccine. The exploration of mRNA’s potential has continued to expand, as evidenced by Moderna’s development of mRESVIA, an mRNA vaccine targeting RSV. These advancements mark a broader shift toward utilising mRNA-based treatments for a wide range of conditions, including infectious diseases, cancer, and genetic disorders.

Biomarkers and molecular diagnostics have become fundamental to personalised medicine, playing a crucial role in identifying genetic variations that influence disease progression and treatment response. Biomarker testing, including companion diagnostics and next-generation sequencing (NGS), is essential for matching patients with the most effective therapies. NGS stands out for its speed, accuracy, and reduced cost and time required for DNA sequencing. Moreover, there has been increasing interest in isothermal nucleic acid detection methods, with loop-mediated isothermal amplification emerging as a faster, more stable alternative to traditional PCR-based diagnostics. Despite these advancements, biomarkers still face challenges related to their instability and low concentrations, which can hamper reliable detection. To address these limitations, synthetic biosensors such as DNA barcoding are being employed to amplify and detect biomarkers, with recent studies also exploring the potential of CRISPR-Cas technology for enhanced precision and sensitivity towards biomarker detection.

Current market and key players

The global personalised medicine market was valued at $529.28 billion in 2023 and is projected to grow at a compound annual growth rate (CAGR) of 8.2% from 2024 to 2030. This growth is driven by the increasing demand for novel drug discovery, particularly for cancer and rare diseases. The widespread adoption of NGS has also accelerated the development of personalised treatments. Additionally, strategic collaborations between pharmaceutical companies and research institutions have fuelled innovation in this field.

Leading companies in the personalised medicine market include GE Healthcare, Illumina, Inc., Abbott, Danaher Corporation (Cepheid, Inc.), QIAGEN, and Exact Sciences Corporation. These organisations are at the forefront of developing cutting-edge diagnostic solutions and investing in research to advance personalised treatment options. Their efforts continue to shape the future of precision medicine, making it more accessible and effective for patients worldwide.

Barriers to personalised medicine

Despite its promise, personalised medicine faces several challenges. One of the most critical issues is the lack of diversity in genomic research. Over 90% of genome-wide association studies have focused on individuals of European descent, limiting the applicability of personalised medicine for other populations. This lack of representation poses a significant barrier to equitable healthcare. Additionally, socioeconomic disparities impact access to advanced genomic testing and personalised treatments, further raising health inequalities.

Data management is another critical issue in personalised medicine. The enormous amount of genetic and health data generated through personalised medicine requires secure storage, accurate interpretation, and strict protection. Healthcare institutions must invest in infrastructure capable of handling large-scale genomic data while complying with strict data protection regulations. Many organisations, particularly smaller healthcare facilities, struggle with the high costs and complexity of integrating AI and big data analytics into their systems.

Regulatory and ethical concerns further complicate the adoption of personalised medicine. Informed consent is essential, as patients must fully understand how their genetic data is used and who has access to it. As regulatory approval pathways are not well established for personalised medicine, this creates further complexity. The risk of genetic discrimination is another issue, with potential implications for insurance, employment, and healthcare access. Comprehensive policies must be established to prevent discrimination and safeguard patient confidentiality. Furthermore, workforce training is crucial, as healthcare professionals require specialised skills to interpret genetic data and incorporate personalised medicine into clinical practice.

Lastly, costs are a major barrier for personalised medicine market. Research and development costs for companies investing in precision medicine is more expensive than traditional medicines due to the requirement of companion diagnostics and genetic testing. The heavy requirement for biomarkers results in the need for larger patient groups and higher costs, both of which are significant barriers. In 2022, the cost of precision medicine treatment in North America averaged to around USD $300,000. Whilst by 2027 it is projected to drop below USD $260,000, it is still an extremely expensive mode of patient care.

Future outlook

Personalised medicine is ready to reshape healthcare by offering targeted, efficient, and patient-centric solutions. As AI, genomics, and biotechnology continue to evolve, medicine will increasingly be tailored to the individual, improving treatment efficacy and patient outcomes. However, addressing key challenges such as improving accessibility, ensuring data security, and establishing clear regulatory frameworks, will be essential to fully realising the potential of precision medicine.

Despite these challenges, personalised medicine is widely regarded as the most promising approach for treating and potentially curing significant diseases. To make this vision a reality, key stakeholders including pharmaceutical and biotech companies, diagnostic firms, regulatory agencies, payers, and policymakers must work together to remove obstacles and provide incentives for continued innovation. By fostering collaboration and investing in cutting-edge research, the healthcare industry can ensure that personalised medicine becomes a standard of care, transforming lives and setting a new benchmark for medical treatment.