Therapeutics discovery: From bench to first in-human trials

The 'Therapeutics discovery: From bench to first in-human trials' conference, held at the King Abdullah International Medical Research Center (KAIMRC), Ministry of National Guard Health Affairs (MNGHA), Kingdom of Saudi Arabia (KSA) from October 10-12, 2017, provided a unique opportunity for experts worldwide to discuss advances in drug discovery and development, focusing on phase I clinical trials. It was the first event of its kind to be hosted at the new research center, which was constructed to boost drug discovery and development in the KSA in collaboration with institutions, such as the Academic Drug Discovery Consortium in the United States of America (USA), Structural Genomics Consortium of the University of Oxford in the United Kingdom (UK), and Institute of Materia Medica of the Chinese Academy of Medical Sciences in China. The program was divided into two parts. A pre-symposium day took place on October 10, during which courses were conducted on clinical trials, preclinical drug discovery, molecular biology and nanofiber research. The attendees had the opportunity for one-to-one meetings with international experts to exchange information and foster collaborations. In the second part of the conference, which took place on October 11 and 12, the clinical trials pipeline, design and recruitment of volunteers, and economic impact of clinical trials were discussed. The Saudi Food and Drug Administration presented the regulations governing clinical trials in the KSA. The process of preclinical drug discovery from small molecules, cellular and immunologic therapies, and approaches to identifying new targets were also presented. The recommendation of the conference was that researchers in the KSA must invest more fund, talents and infrastructure to lead the region in phase I clinical trials and preclinical drug discovery. Diseases affecting the local population, such as Middle East Respiratory Syndrome and resistant bacterial infections, represent the optimal starting point.