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The Future of Precision Medicine- Integrating Functional Approaches for Better Outcomes

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Precision Medicine
4 min read

The future of precision medicine: integrating functional approaches for better outcomes.

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Precision medicine is an approach that considers patients’ individual differences in genes, environment, and lifestyle to personalize medical treatments. In the case of cancer, precision medicine involves the identification of specific molecular traits or mutations that drive tumor growth. This information is then used to tailor the treatment of each individual patient.

“Every tumor is different, and the one-size-fits-all approach doesn’t work for patients,” said Dr. Nikolaus Krall, Vice President Precision Medicine at Exscientia  a recent discussion titled, Precision Medicine: What Does the Future Look Like? He was joined by esteemed panelists, Dr. Dominique Heymann, University Hospital Professor at Nantes Universite, Dr. Juha Rantala, CEO of Misvik Biology, and Dr. Mike Sheldon, Senior Director Scientific Affairs at Sampled.

Despite our understanding of the molecular mechanisms of cancer development, tumor heterogeneity presents a considerable challenge in treating cancer. Molecular precision medicine can be limited in its ability to predict the clinical response of patients to certain drugs, particularly in cases where there is a low response rate or resistance to therapy. This is where functional precision medicine comes into play. Instead of relying solely on molecular traits, functional precision medicine involves testing live ex vivo tissue with various drugs to measure their response. This research provides a more accurate assessment of the effectiveness of drugs, and which ultimately will create a more individualized treatment plan.

Molecular testing is not enough to predict clinical response

One of the challenges of solely using genomic testing for treatment selection in cancer is that not all patients with the same type of cancer have the same mutated genes. The complexity of mutations between patients can make it challenging to identify sensitivity to certain therapies using genomics alone. Dr. Rantala stated, “regarding genetic complexity, we are at the point where we don’t have a very clear view of what the complexity brings. So, there are patient-to-patient differences derived from a number of other mutations within the genome.” There are frequent key driver mutations, as well as a long tail of passenger mutations, which can affect how patients respond to certain treatments. To address this, there is a need for other tools to understand the complexity of mutations and to identify simplified approaches to observe sensitivity to certain therapies.

Promising results from successful implementation of functional testing in the clinic

Functional precision medicine involves testing live ex vivo tissues with a drug to measure how they react and extrapolating to predict a patient’s response. Dr. Heymann stated, “functional testing is really complementary to the genomic approach. You cannot opt to discard the genomic approach by ex vivo functional testing, the complementary approach is the key to the future.”

In 2017, The Lancet Haematology published a study on functional precision medicine in oncology, which aimed to select drugs based on how they affect  human tissues rather than solely on molecular traits. This study was the world’s first successful translation of the functional precision medicine paradigm into the clinic. The study showed that this approach could potentially bring individualized therapies to patients who do not currently benefit from molecular precision medicine, which selects drugs based on specific molecular traits such as mutations in certain genes.

Patient stratification based on molecular testing alone can work well in some cases, but it is not effective for all patients. For example, “AML patients with IH1 or kRAS inhibitor mutations have a response rate of only 36-40% to current treatments,” said Dr. Krall. In contrast, the functional approach showed promise in identifying personalized treatments for patients with heterogeneous tumors, considering the tumor microenvironment and the complexity of the metabolic functioning of the tumor. This approach could allow for the identification of molecular patterns that can be used to develop targeted therapies.

Identifying new targets for therapeutic development through functional testing

While there are molecular tests available, there are cases where there is no clear genetic biomarker. In these cases, functional testing can help identify effective therapies for individual patients. By measuring drug response in live tissue samples, clinicians can prioritize highly effective therapies for patients without clear genetic biomarkers. Tumor heterogeneity and complexity make it difficult to identify biomarkers that can be used for patient stratification. As a result, the field is evolving towards more complex approaches, such as spatial transcriptomics, to identify patterns of molecular expression that can help develop targeted therapies.

Improvements in standardization are needed to increase adoption

Healthcare economics is one of the primary factors that is preventing the widespread adoption of the approach being discussed. Dr. Sheldon stated, “the historic landscape of human bio-sample collection and processing for clinical research has been very widespread and disparate. Individual hospitals or research centers will maintain their own banks of tissues, and they’re processed using their own methodologies without standardization. We need large numbers of biospecimens to make proper inferences about the etiology and progression of disease.”

The lack of standardization in human bio-sample collection and processing for clinical research makes it challenging to compare and analyze data. Establishing resources, including biospecimens, technologies, and quality control measures, is critical to overcome this hurdle. However, the cost of whole genome sequencing remains a major challenge, with new technologies that will reduce the cost per assay but still require significant capital expenditures for the instrument. As such, conversations at the societal and governmental level with substantial funding support are necessary. Additionally, the need for bioinformaticians and clinical-grade reporting pipelines is paramount. Centralized institutions can provide turnkey solutions for hospitals to outsource sequencing and data analysis while maintaining confidentiality and secure reporting. In summary, the adoption of this approach will require significant investments in infrastructure and human resources, making it a complex system to deal with, but end-to-end solutions are possible.

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