Patient Partnerships:

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1. What are the odds that we can discover something to move this case forward?

2. Does the patient have data?

3. Is the data digitally organized and in possession of the patient?

4. What level of DNA sequencing does the patient have?

5. Who has analyzed the data?

6. Is the patient *want* to share their medical data broadly?

7. Is the patient able to co-lead the case (administratively or scientifically)

8. What has the patient done to become an expert at their disease?

9. Does the patient belong to any groups identified as underserved communities?

10. Does the patient have realistic expectations for engaging in this research format?

11. How connected is the patient with Doctors and researchers for their disease?

12. Are there any options available that are considered Standard of Care? 

13. If yes, Why are the Standard of care options unacceptable.

14. How urgent is the patients case?

15. What resources or talent can the patient bring to producing their case?

16. Is the patient comfortable becoming a public face of their condition?

17. Does the patient have a support team around them?

18. Is the patient able to travel?

19. Is the patient able to submit new tissue samples?

20. Are we able to obtain bio-banked tissue samples from original resection.

21. Has the patients story been featured in the media?

22. Is the patient public figure or otherwise well known?

23. Does the patient have the ability to self fund further data generation?

24. What is the patients view on open, collaborative medicine?

25. Is the case scientifically or medically interesting? ie: rare disease or unexplained symptoms.

26. Would the patient be able to enact ideas from the research if new insights were presented?

 

Do deep biological profiling for patients before the hackathon.

• Reveal new treatment paths during the hackathon

• Help set up new drug n=1 trial cases after the hackathon

• Create a journal to disseminate results

Plan

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I maintained that the first three Objectives could be supported by the following activities.

1. If the patient support team (may be, but doesn't have to be, the patient or the patient's physician),

2. can provide complete original data (e.g. WES/WGS, RNA-seq, EMR),

   1. hopefully from the same vendor,

   2. and ideally including parent and/or sibling DNA,

3. which has been verified (e.g. Appendix: Mike D'Amour fastq Validation Process produces this report)

4. and has undergone “standard” pre-processing, (e.g. alignment)

5. which has been verified (e.g. multiple aligners)

6. and if the researchers have done much of their investigation before the hackathon (e.g. I reached out to Clemson before they showed up), 

7. then the hackathon can be used to review, discuss and tweak researchers' results, 

8. identify potential targets 

9. and discuss potential therapeutics

10. both of which have been verified (this step added post TRI-con)

11. and can be proposed to the FDA for approval under their n=1 protocol.

12. After step 5, results can be documented by the participating researchers and organizers (listing sources from steps 1-5 as generously donated & properly credited contributions).

My thesis was that the further down the plan the patients are, the more "FDA ready" they are likely to be.  For example, if the researchers have done the research before the hackathon, then the hackathon becomes a conference where attendees discuss n=1 research results.  If they only have unprocessed patient data, then much of the hackathon is spent doing processing and very little research.  Finally, if the data is not verified, there is a chance that the data quality is poor and if so, then the results are guaranteed to be poor.  This happened to me and It is very discouraging.  So don't try to save money upfront. 

From a patient perspective, Plans like this give potential attendees a realistic expectation of what can be done based on where they are.  It also shows them how to get the most "bang for the buck" by doing a fair amount of work ahead of time.