Personalized Medicine in Cloud Computing Era

1. CSE4095/5810: Personalized Medicine in era of cloud computing Aya Saleh Software Engineer Student Affairs Information Technology Department at UCONN aya.saleh@uconn.edu

2. Motivation • Empirical medicine has been around for decades and still medical services are using it. • Personalized medicine is a new trend that has evolved through past few decades since human genomic project had started. • There’s a need to explore the advancement in area of personalized medicine and integrate it in the context of cloud computing era.

3. Empirical Medicine • Treat patients as one population. • Use symptoms and conventional tests like blood work to define disease and judge severity. • Hardly no predictions for future diseases or consequences of current status.

4. What is Genome?

5. Genomic sequencing

6. Genomic Sequencing

7. Clinical Data • EHR : records for patients..etc. • Administrative data. • Claims : which includes all insurance companies claims, pharmacy and enrollment. • Clinical trials. • Surveys.

8. Clinical Data • Clinical research is mainly: 1) Clinical studies Ex: Researchers may collect data about medical exams, tests, surveys for a specific group of adults to learn about life style effect on cognitive health. 2) Clinical trials Ex: startups like “Trial spark” is working on lessening time and money with advanced technology and analysis by simulating trials and therefore less time and money are spent to get a drug, diet or medical device out.

9. Clinical Data

10. Personalized Medicine The goal of personalized medicine is to achieve patient-centric care through providing tailored healthcare.

11. Personalized Medicine

12. Personalized Medicine • Advances in understanding the genetic basis of individual drug responses come from the NIH Pharmacogenomics Research Network (PGRN) (http://www.nigms.nih.gov/Initiatives/PGRN). Since its founding in 2000, this nationwide alliance of research groups has studied genes and medications relevant to a wide range of diseases like Alzheimer's , cancer , heart diseases and diabetes. Ex: If it is found that a DNA mutation increases a person’s risk of developing Type 2 Diabetes, this individual can begin lifestyle changes that will lessen their chances of developing Type 2 Diabetes later in life.

13. Personalized Medicine • Personalized medicine is called p4 too i.e ( predictive, preventive, personalized, and participatory medicine) • There is an urgent need to bridge the gap between advances in high-throughput technologies and our ability to manage, integrate, analyze, and interpret omics data • An increasing lag has been observed in our ability to generate versus integrate and interpret omics data these last ten years

14. Personalized Medicine • Clinical Sequencing Evidence-Generating Research (CSER2) program, there is an initiative to integrate genomic sequencing into practice of medicine. 1) Define, generate and analyze evidence regarding the clinical utility of genome sequencing; 2) Research the critical interactions among patients, family members, health practitioners, and clinical laboratories that influence implementation of clinical genome sequencing;

15. Personalized Medicine 3) Identify and address real-world barriers to integrating genomic, clinical, and healthcare utilization data within a healthcare system to build a shared evidence base for clinical decision-making.

16. Personalized Medicine • It's not only genetic information that could help in identifying or predicting diseases, there are other factors too like environmental factors. • Precision Medicine: - Identify other factors for treatment than genomics scan and professionally include it. - Genetics study is by population not by Individual. • Precision Health: - Formal naming to precision medicine with information about people’s lifestyles, environments, and communities.

17. Personalized Medicine

18. Legality and ethical issues • Who will really receive the benefits of PM? • Will patients with private insurance and greater disposable income have unfettered access and better health care? • Genetic Information and Nondiscrimination Act - ensuring privacy of information between health care providers, insurers and employers discrimination based on risk factors of genetic information.

19. Cloud Computing

20. Cloud Computing • Cancer research in the era of big data presents major challenges: computing on large datasets, combining expertise from various disciplines, and developing the infrastructure needed to enhance research efficiency.  • The National Cancer Institute (NCI) has initiated multiple projects to characterize tumor samples using multi-omicapproaches

21. Cloud Computing

22. Conclusion • Personalized Medicine - Advancements in the field and challenges in integrating these advancements. - Need to consider other variables like environment, lifestyle , even support groups work in clinical decision support systems. - Ethical and social issues like human-breeding using genomics or ability to have genetic screening under insurance. • Cloud Computing role in fastening integration processes and how to make the world work together on the same topic.

23. Thank you • https://news.nationalgeographic.com/2017/07/dogs-breeds-pets-wolves-evolution/ • https://www.cnn.com/2018/03/14/health/scott-kelly-dna-nasa-twins-study/index.html