Prof. Fabian Schmidt is fascinated by the power of viral adaptation and view 'Virus Learning' as a biological analogue to 'Machine Learning'. Moreover, he is certain that by synergizing these two approaches in automatic processing pipelines, revolutionary improvements can be made at the intersection of synthetic biology and biomedical sciences. At KAUST, his team will start by tackling a major bottleneck that flaws the manufacturing of viral gene therapy vector productions. These vectors are key to accessing cell types and organs in the human body for medical interventions. Yet, manufacturing remains difficult and inefficient even for the most commonly used vector format: Adeno-associated virus vectors (AAVs). Using synthetic biology approaches, they will work on innovative and scalable platforms that address these shortcomings.