373 General Discussion - hiPSC-CMs Disease Modelling and Future Perspectives 13 described, the hiPSC-CM offers a robust and reproducible platform “clinical trials in a dish” (CTiD) with a future reality of commercialization by revolutionizing our thinking about the applications of HTS in the field of drug discovery across the pharmaceutical industry. The implementation of hiPSC-CMs allows the testing of therapeutic targets and hit compounds during the early stages of drug discovery and chemical optimization. Still, any of these deviations could potentially raise differences between lines' subsequent responses and could be an artifact of variation during the screening, rather than a reflection of the underlying biological pathology128. Therefore, we advise increasing and testing the inter- and intra-batches coefficient, thereby allowing the identification of ‘’physiological’’ and ‘’pathological’’ differences. Still, we would recommend the improvement of hiPSC-CM standardization and quality control, as well as clear guidelines for designing and executing any in vitro studies testing therapeutic strategies, including CTiD studies. Then, in the future, it may be possible to study the chronic side effects of prolonged treatment and rare drug effects may be rapidly identified in vitro. One impressive example of in vitro 3D models for personalized medicine is the discovery of rectal organoids in Dutch cystic fibrosis (CF) patients. Within only 4 years, the first person received treatment for CF based on drug efficacy in CF organoid swelling assays.129 Now, over 700 organoid models derived from rectal biopsies of CF patients, representing over 100 clinically relevant mutations, are biobanked.130 The future could hold the potential to biobank every CF patient (1500 in the Netherlands) to improve research and to evaluate in vitro the effectiveness of novel compounds. Instead of subscribing to a drug based on the largest statistical population, these CF organoids could be cheap avatars for a patient’s personalized disease modeling, characterizing the disease even before these young patients develop symptoms. However, only five classes of CF gene mutations exist to disturb protein production, processing, gating, conduction, and function. Therefore, the in vitro modeling and screening of cardiomyopathies might be far more challenging, considering that over 50 individual genes (and counting) are affected, causing completely variable pathophysiological phenotypes such as DCM, HCM, and ACM.131–134 Still, the impressive CF in vitro disease modeling set the example for the future of personalized medicine in individuals with a risk of developing heart failure. The generation of such a system will not only help patients but will also allow prevention of the onset of the disease and predict the drug efficacy and toxicity for each individual.135 This allows cardiologists to move from the current 6 types of standard heart failure medication to the best match for treating or even preventing the disease as early as possible. In summary, the work described in this thesis has contributed to a realistic view of the possibilities and current limitations of hiPSC-CMs for the disease modeling of genetic cardiomyopathies. While keeping eventual clinical implications in mind, hiPSC-CM research was taken from the basic to the translational level (Figure 5). The journey from many hiPSC lines to the HTS of thousands of spheroids that predict the disease and potential therapeutic targets is paving the way for the future of predicting, preventing, and personalized medicine of all cardiomyopathies.
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