Following the recent news that Valo Health and Kahn-Sagol-Maccabi (KSM) will perform joint studies using KSM’s Tipa Biobank^TM of more than 800,000 samples and Valo’s drug discovery and development platform Opal^TM;

Ashley Clarke, Medical Analyst at GlobalData, a leading data and analytics company, offers her view:

“The collaboration provides an opportunity to utilize the growing patient data sector to capitalize on the race to get drugs designed using artificial intelligence (AI) to market. AI and big data are transforming healthcare with high-throughput analysis of complex diseases. Machine learning and sophisticated computational methods can be used to efficiently interpret human genomes and other biomarkers, providing insights for patient treatment and with major applications in diagnostics and preventive care.”

GlobalData’s report, ‘Precision and Personalized Medicine – Thematic Research’, notes that, historically, clinicians have used factors such as symptoms and medical history of a patient throughout the diagnostic and treatment phase. While this is still helpful information, these factors alone tend to favor a “one size fits all” approach in medicine. With the use of precision and personalized medicine, clinicians will not only consider symptoms and medical history, but also the patient’s genetics, environment, biomarkers, and more.

Clarke continues: “Human data can be studied to bypass some of the limitations of conventional cell and animal models. Bioinformatics and big data provide a vast collection of human-centered information that can be used in lieu of or in combination with conventional models to streamline the drug discovery process and reduce the time spent on inviable drug candidates. For example, laboratory mice have historically been utilized in early phase drug trials, but they are a poor model for genetic diversity and age-related diseases in humans.

“The Tipa Biobank^TM stores ‘live’ samples, and the company plans to continue collecting genetic samples from the same subjects over the course of their lifetimes. This could give Valo/KSM a competitive edge for developing treatments in oncology and for neurodegenerative diseases.”

GlobalData’s report also notes that increased competition and advances in technology are driving down the cost of genetic sequencing. Physiological data is also more comprehensive and accessible than ever due to the recent growth of remote patient monitoring devices and wearable tech from the COVID-19 pandemic.

Clarke concludes: “Looking to the future, the accessibility of genetic and physiological data will help paint a clearer picture of overall patient health. The demand for preventative medicine will continue increasing as people are living longer and the global elderly population is growing. Precision and personalized medicine also has potential to improve disease screening and predict patient responses to treatment options, leading to improved quality of care and reduced overall healthcare costs.”