Rare genetic disorders are collectively common specifically in Saudi Arabia because of the high rate of consanguinity. There are a quite virtuous progress in development of drugs for rare genetic disorders. However, the biggest challenge to rare genetic diseases drug development by far is the small size of rare disease populations. Patients with these progressive, serious, life-limiting and life-threatening diseases are often geographically dispersed, which can make it difficult to find enough patients able to reach clinical trial sites. Additionally, it can be difficult for medical practitioners to develop expertise in conditions that are seen so rarely. This often results in a consolidation of expertise at a single or few locations that may be challenging for some patients.
The FDA recognized these challenges and started support to the people affected by rare diseases by accelerating, supporting and facilitating the process of getting orphan drug products to market. In 2016, FDA announced the availability of $2 million in research grants to fund natural history studies in rare diseases. The aim is to collect data on how specific rare diseases progress in individuals over time so that knowledge can inform and support product development and approval. This will be the first time the FDA will provide funding through its Orphan Products grants to conduct these types of studies for rare diseases. Artificial intelligence (AI) is the simulation of human intelligence processes by machines, especially computer systems. These processes include learning (the acquisition of information and rules for using the information), reasoning (using rules to reach approximate or definite conclusions) and self-correction. Recently, it is prove its application in drug discovery. Leading biopharmaceutical companies believe in this new approach. Pfizer is using IBM Watson, a system that uses machine learning, to power its search for immuno-oncology drugs. Sanofi has signed a deal to use UK start-up Exscientia’s artificial-intelligence (AI) platform to hunt for metabolic-disease therapies, and Roche subsidiary Genentech is using an AI system from GNS Healthcare in Cambridge, Massachusetts, to help drive the multinational company’s search for cancer treatments. Most sizeable biopharma players have similar collaborations or internal programmes. Developing expertise in AI for rare genetic disorders is a unique goal that will accelerate drug discovery for such disorders. In conclusion: AI is a new paradigm in medicine and it is application in drug discovery for rare genetic disorders is exciting and need to be explored.
Building 9 - Lecture hall 2
10:50 - 11:25