2008 Decisive Math

Good afternoon all, I come from the chemical physical world: just working with immunoassays one learns to respect statistics and probability. Further, working in a multiplexed high throughput manner, data acquisition becomes shortly directed to algorithmic processing steps and away from the immediate human decision. Not to downsize the chemical and physical worlds, I need to remind you all that today sequencing is done simply by measuring pH during the DNA synthesis. Yes, using CMOS based computer chips but still measuring nothing else but a pH change.

So math and IT dominate the data processing, chemphys problems with nanosize precision give the info in quality format, the remaining tasks are within the genomic world: the medical doctors. The present medicine is based on evaluating symptoms, when compared to an average patient case. MDs like to discuss deviations from the average but dont realize how decisive an individual data change can be. For instance an observed weight change for an 80 yo person results in a cancer analysis but unfortunately often with the disease recognition too late. Weight change is still based on quite simple mathematical expression and be handled by MDalgebra so continuous monitoring would have revealed the information earlier.

The future relies on genomic evaluation, associations and comparison on population, culture and individual levels. A change analysis, within mutations and other single gene properties, pioneers to novel information access. Drug design as an immediate example, mutations along the cancer pathways, guide to optimal drug usage.

Last year in the Annual American Medical Society meeting nearly all doctors agreed on the importance of genetic information on health and medicine. But less that 10% of the doctors knew how to use the information for assigning prescriptions. The remaining link will be between decisive math and medical doctors, the assurance of data processing is not the only issue is thus guiding impact for proper used in the critical issue,

This can be solved by proper education mainly in the field of bioinformatics where creating the new knowledge is not the only goal but development of workforce for vat data procession will expand to novel types of employment in doctor’s office and to novel commercial efforts like eQuest.

The talk was given as a panelist at the Courant Institute’s 75^th anniversary.