Dr. Talia Cohen Solal uses a microscope to examine human brain cells that have been cultured in a petri dish up close.
The brain is extraordinarily nuanced, intricate, and lovely, she claims.
Israeli health technology company Genetika+’s co-founder and CEO is neuroscientist Dr. Cohen Solal.
The company, which was founded in 2018, claims that its algorithm can best match antidepressants to patients, avoiding unpleasant side effects and ensuring that the recommended medication functions as effectively as possible.
Dr. Cohen Solal continues, “We can identify the appropriate medication for each patient the first time.” Genetika+ achieves this by integrating cutting-edge artificial intelligence (AI) software with stem cell technology, which involves the growth of particular human cells.
Its technicians are capable of producing brain cells from a patient’s blood sample. These are then subjected to various antidepressants while “biomarkers” of cellular alterations are being monitored.
An AI system processes this data along with a patient’s genetic information and medical history to choose the most appropriate medication and dose for a doctor to prescribe.
The technology is still in the development stage, but Tel Aviv-based Genetika+ plans to make a commercial debut the following year.
The startup is an illustration of how AI is increasingly being used in the pharmaceutical industry and has received financing from the European Research Council and European Innovation Council of the European Union. Additionally, Genetika+ collaborates with pharmaceutical companies to create novel, precise medicines.
The business anticipates future growth in demand for its products. The World Health Organisation estimates that there are over 280 million depressed persons worldwide.
Additionally, it has long been believed that nearly two-thirds of initial prescriptions for depression or anxiety may not be effective, even if taking antidepressants is undoubtedly not the best course of action for everyone.
According to Dr. Cohen Solal, “We are living in the best time, at the best place and into the best moment when we have the capability to merge biological technology with the latest computer technology.”
According to Dr. Heba Sailem, AI has a significant potential to alter the global pharmaceutical business, which is expected to produce $1.4 trillion (£1.1tn) in revenue by 2021.
At King’s College London, a senior lecturer in biomedical AI and data science, claims that AI has so far aided in everything from “pointing as well as identifying a targeted gene as to treat a particular disease and discover a new drug, to enhance the quality of the patient treatment for making predictions about the best treatment strategy as well as making discoveries about the biomarkers for the personalized treatment of the patient, and also for the prevention of development of any gene related disease for treating a certain disease. Thus, it will give us the authority and knowledge to discover and make a new drug.
However, according to a different AI expert, Calum Chace, the adoption of AI in the pharmaceutical industry is still “a slow process”.
“It’s challenging to get everyone to agree to a fundamentally different way of doing things, in part because senior people rose to their positions by following the established norms.
They are accustomed to it and believe it. Additionally, if the value of what they can accomplish suddenly declines, they can worry that they will become less useful to the company.
