Designing a new pharmaceutical drug typically costs billions of Euros, and the entire path from research to market often takes many (>10) years, with several obstructions which often provoke failure of the entire process. In particular, often a drug which performs well in laboratory (“in vitro”, or on isolated tissues, i.e. “ex vivo”) fails the subsequent testing phases (“clinical trial”) on animals and human patients (“in vivo”). Such advanced drug testing phases may last several years and often are extremely expensive, as the involvements of animals and human patients requires great care about safety and security.

A late failure of the verification process for a new drug (for example, during the “in vivo” phase) implies a huge economic loss for the drug developers (for example, a pharmaceutical industry). This leads to the fact that pharma companies are often rather conservative in starting research activities on radically innovative drugs.

One of the most revolutionary research directions in medicine and pharmacology consists in defining and exploiting mathematical models of the human physiology (“Virtual Physiological Human”, VPH) in order to design and verify safety and efficacy of new drugs and new treatment protocols “in silico” (i.e., by means of computer simulation), before starting expensive, risky and invasive “in vivo” clinical trials on animals and humans.

The main objective of a VPH model is to capture all biologically correct behaviours, that is all behaviours that could occur in nature. By combining clinical data on real patients (e.g., from blood samples) and sophisticated computational techniques from Artificial Intelligence, such models can be individualised in order to make them able to simulate the behaviour of any given patient and his/her personal reaction to a set of drugs. The possibility to individualise VPH models also allows “in silico” design of individualised pharmacological therapies, i.e., therapies that maximise their performance on a certain given human patient at the same time minimising expected risk and severity of negative side-effects.

Summing up: success of “in silico medicine” will lead to the following achievements with huge technical, economical, social and ethical impacts:

• A great reduction in the number of animals and human volunteers in clinical trials for testing new drugs and treatments.
• A great reduction in the duration and costs of new drug design and verification activities. This would also lead to a great reduction of the costs to be paid by national Public Health Systems and, as a consequence, by taxpayers (currently expenditures in Health is by far the highest item in national budgets), and, ultimately, in moving these enormous economic resources into research of radically innovative drugs.
• The possibility to design optimal treatments for any single patient, which maximise the clinical outcome on that patient at the same time minimising risk and severity of side-effects as well as the quantity of drugs used.

During the Honour Programme, students will learn methods based on Artificial Intelligence in the context of “in silico medicine” in order to design and verify safety and efficacy of individualised treatment protocols, exploiting complex VPH models.