1. Topic: Medicine of the future Reading: Harbron, Chris (2006)
Topic: Medicine of the future Reading: Harbron, Chris (2006). Statistics and the medicine of the future. Significance 3 (2), Group 5: Shu Min, Yan Ling (Presenter), Yi Mou

2. Outline Development of medicine through the years
Development of technologies for personalized medicine
The role of statistics
Challenges
Future outlook

3. Development of medicine
Water Retention

4. Development of medicine
One pill has to fit all
In trials of new drugs, when a small proportion react badly to them, the new drug will be rule out of use and unavailable to everyone

5. Personalized medicine?

6. Omics
The pharmaceutical industry is looking into the development of a range of new technologies known as the “omics”
Refers to a field of study in biology that ends in –omics, such as genomics or proteomics
Aim to understand mechanisms of disease and examine cell processes at a very detailed molecular level

7. 20,000 genes in the human genome
Omics
20,000 genes in the human genome
Genomic technology
- identify associations of genes
with any disease/drug responses
Proteomic technology
-identify the proteins that result in
the progression of the disease
3 million different human protein species

8. Large datasets
So how?

9. The role of statistics
To organize, analyze and make inference from the data

10. Challenges
Difficult to identify biases or outliers in the data of these small molecules
Multivariate predictive modelling
Efficiently process large quantities of data, adapt algorithms to cope with the size of the dataset

11. Challenges – Interpretation of results
“With so many different analytes, whether they be genes, proteins or metabolites, some false positives of highly significant associations are likely to appear by chance.”

12. Challenges
Comparisons for the testing of multiple hypothesis (Classical method: Bonferroni method)
In medical testing, the false discovery rate is a more powerful test than the Bonferroni method.
The false discovery rate accepts that you will select some differences between groups as interesting and assesses the quality of these differences and their likelihood of being genuine.
Attach biological meaning to the statistical results

13. The future This area of personalized medicine has great potential
Difficult to find new drugs that are safe and effective for all
Development of omics technologies to ensure continuing improvements in medical treatment
Technical and practical challenges of handling complex data, challenge of interpreting and attaching biological meaning to these results
Collaboration of many disciplines

14. Thank you!

15. References http://www.statisticshowto.com/conservative/
onalizedMedicine/UCM pdf