Study Rationale:
Experts from various biomedical fields are trying to identify treatment options for Parkinson's disease, but approaches that target a single gene or mechanism have thus far been unsuccessful. Moreover, scientific data and literature are published at a dizzying pace that has outgrown human capabilities to keep up and synthesize all the information. Finding and combining important bits of information and coming to breakthrough conclusions fast is one of the biggest challenges in science right now. We want to overcome this challenge with the help of artificial intelligence.
Hypothesis:
Our intelligent software can read and comprehend millions of scientific documents from hundreds of key knowledge domains -- such as publications, patents, or medical trail reports -- to augment hypothesis generation and scientific decision-making.
Study Design:
In cooperation with The Michael J Fox Foundation, we develop smart user interfaces to evaluate the state of the art of Parkinson's research. By analyzing the wealth of knowledge in decades of research data, we will identify emerging key domains, technologies and druggable disease targets that were unknown or underappreciated in the past. We use state-of-the-art natural language processing that allows us to read and comprehend scientific text automatically and analyze millions of documents at the click of a button. This condensed knowledge will be made available to MJFF researchers to inform their decision-making for funding and discovery.
Impact on Diagnosis/Treatment of Parkinson's Disease:
The potential of our novel approach lies in the new connections we will find between different scientific domains, experimental models and research approaches. By analyzing all of the research done so far, our artificial intelligence will help scientists identify future directions much faster.
Next Steps for Development:
Once we identify promising new drug targets, molecules or experimental systems, we will help MJFF support research with the highest potential and thus accelerate the discovery rate of breakthrough therapies.