Traditional oncology treatments were designed to rapidly kill fast proliferating cells in a one-size-fits-all. However, once the first draft of the human genome was completed in 2001, a new era of genomic analysis of patient tumours became a practical reality. Cancer centres and commercial entities began matching patients genomic sequencing to the drugs that would treat their individual tumours. Precision medicine was born.
A literature search using “precision medicine" as keywords shows an exponential increase over the years. According to the National Cancer Institute (NCI), the words refer to a therapeutic strategy for a group of people with similar genetic patterns, lifestyles, environmental and cultural factors and therefore likely to display similar response to therapy. Personalised medicine is an evolution of this concept that required the understanding that, although they may share genetic similarities, each patient is unique and may present a different clinical picture and response to therapy.
Whereby precision medicine is a paradigm that can be modelled at the preclinical stage taking a population approach based on the similarities shared by a subset of patients, personalised medicine is a more resource intensive and dedicated clinical approach to therapeutic development that still requires clinical trial experimentation.
Precision medicine has evolved and improved over the years, especially in the field of oncology that is leading precision medicine approaches through the development of pathway-based targeted therapies. Targeted therapies such as the small-molecule kinase inhibitors, imatinib, gefitinib, or erlotinib have significantly improved treatment outcomes for recurring or refractory cancer patients with leukaemia, lung, melanoma, or pancreatic cancer.
At the preclinical stage precision medicine approached can be modelled using a library of well-characterised patient-derived cell models that recapitulate the diversity observed in the patient population. These models are used as patient avatars to test the anticancer efficacy of new drugs, to refine combination strategies, or identify biomarkers of response.
Additionally, the technological advances achieved over the part 20 years have enhanced the use of patient-derived cell models. For one, we have much better and more varied culture systems for the study of patient samples ex vivo in both two-dimensional and three-dimensional formats. We also have more and better assays to measure perturbations induced by drug exposure. We have the ability to study single cells in detail and have vastly improved bioinformatics capabilities that allow the combination of complex drug response data with any number of clinical and molecular biomarkers.
To find out more about Imagen precision medicine preclinical platform head to predictTx
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