Personalized medicine

Health Care Providers need to understand the patient’s genetic profile and get familiar with new technologies in order to personalize their approach to disease prevention, diagnosis, treatment, and management. However, lack of expertise in genomic testing is a key obstacle to precision medicine, many physicians struggling to accurately interpret test results without specialist assistance. Thus, a 2018 survey of 160 oncologists by Cardinal Health found that 60% of physicians who do not use genomic tests avoid them because of the difficulty of interpreting the genomic data.

How to educate and train HCPs to ensure an effective use of these new technologies? How to re-think the whole care organization in oncology and genetic disease in order to include precision medicine protocols? How will evolve the HCPs role and responsibilities – especially oncologists’- in the next future and how to support them? How to ensure hospitals hire the right specialists to support physicians in deciphering the data?

The expansion of Big data (e.g. Multi-omics, images, device data, electronic health records…) is an obvious key driver of personalized medicine, and the creation of powerful systems to analyze it requires massive scientific and technical developments, in which multiple stakeholders have a role to play. Pharma and diagnostic companies need to rethink their R&D strategies to better understand diseases at a molecular level, develop tests to analyze genetic data and invest in tools to interpret it. They can also develop innovative partnerships; one key example being Roche’s partnership with Illumina in January 2021 to broaden the adoption of distributable next-generation sequencing (NGS) based testing in oncology. Governments also have a role to play by driving efforts in building genetic data sets and biobanks. Former US President Barack Obama launched for example the Precision Medicine Initiative in 2015; (which then became the “All of Us research program”), aiming at gathering health data from more than a million US volunteer-citizens.

Who will be the key stakeholders to partner with in the next future? How will the market for future tests evolve and how to be ready on time? Will the value lie in the test itself or in the insights generated?

Personalized medicine is based on individuals’ data, collected with diagnostics and behavioral devices. Therefore, some security concerns naturally arise regarding the way this data is used. Thus, the use of personalized medicine must be accompanied by appropriate basic policies, frameworks and tools. On the other hand, patient data privacy is dealt differently depending on the country, and stringent local data protection regulation could jeopardize the personalized medicine momentum.

How to ensure personal data protection when sharing them is needed to ensure patient care and research progress? How to deal with different national or regional data privacy regulation? How to educate patients on the need to share their genetic information for medical research?

The tremendous clinical benefit of personalized therapy has a cost: molecular diagnostics can be hundreds to thousands of dollars and are not always reimbursed, therapies themselves can cost up to hundreds of thousands of dollars a year. In the 2018 Cardinal Health study, many participating physicians said payers’ failure to cover the costs of genomic tests was as a common barrier to adoption of genomic testing. The pharma industry needs therefore to partner with payers to develop new and affordable business models around personalized therapies. These should include appropriate reimbursement of molecular diagnostics, of the targeted therapies themselves, and of other personalized treatment protocols, to incentivize the practice of personalized medicine.

Which commercial model should be developed around precision medicine therapies? How to ensure access equity for all patients? How to define the best commercial model when smaller and smaller patient populations are considered? Who will own the future value of these therapies? Will traditional blockbusters markets become less profitable than smaller and exclusive markets of personalized medicines?

Precision medicine is changing the way clinical trials are and will be set up. As genetic testing helps create subtypes of diseases (like HER2-positive or triple-negative breast cancer), it is possible to test one drug on a big group of patients with different known types of the disease. In parallel, trials can also test targeted therapies specifically designed for patients with one given genetic variation. Thus, the use of one-person trials, known as “n of 1 trials,” is supporting personalized medicine research. The response rate is therefore likely to be higher as the studied treatment will target just one aspect of disease, for example one specific genetic mutation, that all the patients involved in the trial will have. By studying only people who can respond, researchers maximize the chance of good results.

How to re-design clinical trial to adapt to precision therapies? Will smaller trials with better results mean faster drug approvals?