Translational medicine can be defined as ‘the process of applying ideas, insights, and discoveries generated through basic scientific inquiry to the treatment or prevention of human disease’. This is also known as taking research ‘from the bench to the bedside’.
The gap between basic science at the laboratory bench and clinical science – the human studies of therapeutic and diagnostic drugs and devices – is sometimes referred to as the valley of death, because in vitro and in vivo studies don’t always effectively reflect what will happen in clinical trials, meaning that only a small fraction of the drugs that succeed in preclinical studies and enter clinical trials actually make it all the way to approval and the market. [1-3]
In order to bridge this so-called ‘valley of death’, researchers are developing new translational models designed to better predict the efficacy and safety of potential therapeutics in healthy volunteers and patients in clinical trials.
In vitro translational models: Clinical responses in a test tube
An organ-on-chip (OoC), also known as a microphysiological system (MPS), combines natural or engineered human cells with microfluidic chips and sensors to create an in vitro model of a human organ, such as a heart, lung, kidney, lymph node, bone marrow or liver, which can be used in real-time drug testing. An OcC can predict how drugs may behave in clinical trials, as well as allowing researchers a better understanding of disease mechanisms and drug responses. [4-6]
Clinical trials in dish (CTiD) allow researchers to screen potential clinical candidates in human cells from the planned patient population, getting early indications of safety and efficacy and creating a bridge between preclinical testing and clinical trials. The clinical trial in dish is based on induced pluripotent stem cells (iPSCs), whole genome sequencing and organs-on-chips. The use of patient-derived or genome-edited iPSCs mean that the CTiD can be tailored to a specific disease or a particular individual. [5]
Organoids are three-dimensional miniature organs that self-assemble from single or multiple adult or pluripotent stem cells or are 3D bioprinted using ‘bioinks’ that combine cells and biocompatible materials to create complex models that more closely mimic the tissues being tested. Examples include 3D bioprinted tumour models that include the tumour microenvironment, or complex tissue models along with the associated vasculature. The US Food and Drug Administration has recognised organoids as an alternative to animal studies as the step before clinical trials. [5, 6]
In silico translational models: Virtual reflections of human responses
Computational modelling and simulations can predict how drugs will interact with tissues and cells. Examples of in silico models range from how drug molecules bind with receptors to how they interact with entire biological systems or pathways. By incorporating biomarker data, researchers can create patient-specific models to predict outcomes in personalised medicine. [6]
Artificial intelligence and machine learning can use large datasets, such as literature databases, clinical trials databases and electronic patient records (EHRs) to create models to predict how new drugs interact with targets or disease mechanisms, or simulate clinical trials. [6]
A digital twin, a term that has arisen from the aerospace industry and is used in many areas in engineering, is a virtual model of a physical entity in its environment, with the two connected and exchanging data in real time. Digital twins in healthcare are virtual versions of the organs of real patients based on actual patient data and play a role in medicine by supporting healthcare professionals in planning and optimising treatment strategies, including personalised care. Digital twins have potential in drug R&D to identify drug targets and predict treatment outcomes in animal studies potentially reducing the number of animals required. They can also mimic huma...
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