Cellular Models of Disease
Given that 90% of drugs in development fail to achieve approval – with 60% of this attrition due to lack of efficacy in clinical trials – new approaches to therapeutics discovery are needed. The cell can be viewed as the fundamental unit of disease where phenotypic readouts integrate information from intrinsic and extrinsic sources: the genome and epigenome along with the molecular and physical environment. In order to understand disease and discover new therapies, we need preclinical models that faithfully represent patients. Furthermore, we want to be able to interrogate biological states and behavioural responses at multiple scales potentially simultaneously – working at the subcellular, cellular, tissue and organ levels.
The identification of adult stem cells and methods to grow them in vitro, so called ‘organoids’, as well as directed differentiation of embryonic stem cells, patient-derived iPSC technology and precision genome engineering have transformed our ability to generate myriad cell types in both the diseased and healthy states and recapitulate at least some aspects of disease in vitro. Recent organoid clinical studies have shown that these patient derived models are directly representing the clinical responses of the associated patients. In addition, the advent of 3D culture in vitro is now opening up the possibility of near-physiological tissue organisation that increasingly is resembling other aspects of the native function. Together, the new models represent a powerful in vitro platform for preclinical drug discovery and validation and a tool for precision medicine as well as finally allowing the long-term promise of personalized medicine. In this session we will cover a range of different examples of uses of these advanced systems and give attendees insights into this rapidly developing area of biology.
Chemical biology – re-defining target and therapeutic class tractability?
In recent years chemical biology approaches have re-defined therapeutic class and chemical tractability of proteins. Notably, event-driven pharmacology and novel classes of therapeutics offer great promise for targets previously considered undruggable. In this session exciting new concepts in chemical biology and opportunities for drug discovery with tangible potential to improve patient health will be discussed.
Big Data and Artificial Intelligence
Artificial Intelligence (AI) is now being applied everywhere at least according to the news. Needless to say that also includes drug discovery. In this session we would like to give the audience a sense of what is going on in applying AI and machine learning (ML) in drug discovery by covering several important aspects. The background and historical development of ML and AI in drug discovery will be presented. We will also take a look at the most important ingredient to successfully apply ML and AI in drug discovery project, namely the data and how it can be integrated. Applying ML to large datasets is an important topic that pushes the current machine learning algorithms to the limit. Another important topic to be covered is the integration of ML/AI with automation and the sizeable synergy effects when combining them. Finally, application of deep learning in drug design has now become common, so it is time to hear from a medicinal chemist expert if there has been any real impact on the drug design process or if it just has been another hype.
Targeting Ion Channels for Drug Discovery hosted by the British Pharmacological Society
Drugs targeting ion channels are an important component of many medicine cabinets, but over the past 10-15 years active programs targeting ion channels in the pharmaceutical industry have fallen and a perception may exist that these are difficult proteins to drug. However, significant progress in understanding ion channel pharmacology and structure is being made, which leads us to suggest that this target class is currently being under exploited. Therefore, in this symposium we will look at some of the recent progress in targeting ligand and voltage gated ion channels in disease.