Advancements in cell and gene therapy hold promise for the future of personalized medicine, especially for cancer treatments. However, bioprocessing methods for autologous cellular therapies, and CAR-T in particular, often present unique challenges in manufacturing due to the variability of the starting material and unique nature of each batch. Is there a way to create more efficient processes in order to bring down costs and make personalized medicine a viable option for more patients?
Could data analytics aid in the diagnosis of severe neurological diseases? In a recent study, a research group at Umeå University has conducted statistical data analysis of biomarkers from patients suffering from Amyotrophic lateral sclerosis (ALS, also known as Lou Gehrig’s disease) and Parkinson’s disease to investigate whether data analytics could help in the diagnosis of – and help distinguish between – the two diseases.