Yale: Immuno-onc lots of attn - how does it translate to other conditions? Florez: T1D risk scores on HLA; promising for trtmt #PMLS2016
2:24pm August 11th 2016 via Hootsuite
Palmer: Can't overest. the complexity of these systems; so you measure everything you can measure. #PMLS2016
2:18pm August 11th 2016 via Hootsuite
Kurzrock: Genomics improvement over proteomic markers - about 2-fold. And - matched Rx showed worse outcome #PMLS2016
2:16pm August 11th 2016 via Hootsuite
Kurzrock: 'Proteomics is helpful but genomics is a better predictor'. Meta-analysis 85K pts biomarkers. Better outcomes w/matching #PMLS2016
Ganz: JAMA '16 https://t.co/xmMH0Pd10s w/proteomic risk scores, but analyzed w/traditional rather than newer statistical mthds #PMLS2016
2:14pm August 11th 2016 via Hootsuite
Moderator Ken Yale (Active Health Mgmt, Aetna) An advocate within Aetna. Ganz: for Cardio, complex, only risk scores, not binary #PMLS2016
2:12pm August 11th 2016 via Hootsuite
Florez: Genomes are cheap, finite, precise (as compared to other analytes); less dependent on environment #PMLS2016
2:08pm August 11th 2016 via Hootsuite
Jose Florez (Harvard) Germline genomics is measured only once Peter Ganz (UCSF) Makes the case for proteomics, metabolomics #PMLS2016
2:06pm August 11th 2016 via Hootsuite
Kurzrock: Cancer is at the forefront of Pers Medicine, but can apply lessons across the board to many other diseases #PMLS2016
2:04pm August 11th 2016 via Hootsuite
Razelle Kurzrock (UCSD), was at MDAnderson building clinical trials dept there; started genomics w/cancer in '07. Need for comb Rx #PMLS2016
2:03pm August 11th 2016 via Hootsuite
Palmer: GPS is four parts: WGS, RNA, amole resolution of 27 protein analytes, and somatic mutation from blood #PMLS2016
2:01pm August 11th 2016 via Hootsuite
Eric Lai (Takeda) gives bkgd, Gary Palmer (NantHealth) describes GPS test; was at Genomic Health (Medical Affairs) and Foundation #PMLS2016
2:00pm August 11th 2016 via Hootsuite
#PMLS2016 now has a five member panel "Pragmatic Implementation of Precision Medicine Approaches for Major Diseases"
1:57pm August 11th 2016 via Hootsuite
Kolodziej: The payer doesn't have the architecture to evaluate evidence. Optimistic they will act on clin utility data. #PMLS2016
1:13pm August 11th 2016 via Hootsuite
Kolodziej: Mention of TAPIR and MATCH - use info to guide dev and reimb policy. Rx is straightforward - w/CDx or not. PMLS2016
1:12pm August 11th 2016 via Hootsuite
How can physicians be supported better? Dracopoli: Much larger population-level dataset, with diversity of patients #PMLS2016
1:11pm August 11th 2016 via Hootsuite
Kingsmore: "We're changing the world, helping one kid at a time; let's do it." #PMLS2016
1:01pm August 11th 2016 via Hootsuite
What do we need to do? Kolodziej: We need to test every patient, and record every outcome. Kingsmore: 'I'm not pessimistic at all' #PMLS2016
Kolodziej: Bristol's cost of hype - 'we can't solve our problems with the same thinking we used when we created them' #PMLS2016
12:58pm August 11th 2016 via Hootsuite
Kolodziej: May need to change to n of 1 reimbursement strategy. Need to figure it out now - due to upcoming cfDNA, multi-omics #PMLS2016
12:57pm August 11th 2016 via Hootsuite
Kolodziej: TAPIR, other trials are ongoing. Payer wish list: Std'ize testing, mandate proficiency, curate/validate catalog of muts #PMLS2016
12:56pm August 11th 2016 via Hootsuite
Kolodziej: BRAF for melanoma, fine. Lung ca - often. But anything else? '15 JAMA https://t.co/DDHwZldSPq #PMLS2016
12:55pm August 11th 2016 via Hootsuite
Kolodziej: 43 additional genes? Foundation Med on most prevalent mutations - TP53 and KRAS? (adenocarcinoma unk primary) #PMLS2016
12:52pm August 11th 2016 via Hootsuite
Kolodziej: 81445 - how well is it being done? Many 'peddling this stuff on price'. A 4-fold difference! Jiffy Lube or Dealership? #PMLS2016
12:51pm August 11th 2016 via Hootsuite
Kolodziej: Why are payers skeptical? Analytic validity, clinical validity, clinical utility, overall value? "81445" means...? #PMLS2016
12:50pm August 11th 2016 via Hootsuite
Kolodziej: Cost of new oncology drugs, and PFS and OS: correlation of 0.1 #PMLS2016
12:49pm August 11th 2016 via Hootsuite
Kolodziej: How to payers look at this? Differently. Starts with charts on cost of drugs over time: logarithmic scale! #PMLS2016
12:48pm August 11th 2016 via Hootsuite
Michael Kolodziej (Flatiron Health): Why payers are skeptical about PM in oncology and how we can fix that #PMLS2016
12:46pm August 11th 2016 via Hootsuite
Samuels: 'A test that changes physicians behavior' - tying clinical utility to the big picture in patient care. #PMLS2016
12:45pm August 11th 2016 via Hootsuite
Samuels: Dx developers face payer demands for value. Clinical utility 'is the only way to become covered'. #PMLS2016
12:44pm August 11th 2016 via Hootsuite
Samuels: But 'not everyone likes MolDx' - what recourse at a high level, instead of at the local level? Foundation - opens NC lab #PMLS2016
12:43pm August 11th 2016 via Hootsuite
Samuels: Palmetto MolDx 'is seen as a leader' with significant experience in PM #PMLS2016
Samuels: MolDx covers 44% of the Medicare market; in talks to expand; calculation for payment is transparent. #PMLS2016
12:42pm August 11th 2016 via Hootsuite
Samuels: PAMA may enable alignment of payment, PM initiatives. Supports more spec iterative coding; potentially reward innovation #PMLS2016
12:41pm August 11th 2016 via Hootsuite
Samuels: PAMA unclear if alleviate coverage and payment challenges for Dx. 75% of list price; make the case to payers like drugs #PMLS2016
12:40pm August 11th 2016 via Hootsuite
Samuels: Coding and payment has changed five times in 3 years. Trends: drug pricing an issue; reimb is 'perennial challenge' #PMLS2016
12:38pm August 11th 2016 via Hootsuite
Marc Samuels (ADVI) Policy environment: Payer environment - Palmetto, FoundationMed and Exact Sciences Parallel Review #PMLS2016
12:32pm August 11th 2016 via Hootsuite
Kingsmore: Concludes with figure from this '16 JAMA ref 'PM and a Learning Healthcare System' https://t.co/WKxPI8weRj #PMLS2016
12:30pm August 11th 2016 via Hootsuite
Kingsmore: Clinical utility? Ave of 2.9 QALY saved per newborn WGS #PMLS2016
12:26pm August 11th 2016 via Hootsuite
Kingsmore: 115 babies, 57% Dx rate. One from Kansas City, another from AUS - same Dx rate (it is selected, but promising) #PMLS2016
12:24pm August 11th 2016 via Hootsuite
Kingsmore: Will it scale? "We don't yet know." He can't fault the payors: we need to give high-quality evidence. #PMLS2016
Kingsmore: Compound heterozygous, in Perforin 1. Dx: hemophagocytic lymphohistiocytosis. Coagulopathy resolved on day 7. 79 QALY #PMLS2016
12:23pm August 11th 2016 via Hootsuite
Kingsmore: A standard Human Phenotype Ontology, parsed against 8K diseases, model for best fit. Need more data / need for refining #PMLS2016
12:22pm August 11th 2016 via Hootsuite
Kingsmore: 1.1K mutations candidate disease causing var's. Has a computer-generated extracted list of 341 potential Dx #PMLS2016
12:21pm August 11th 2016 via Hootsuite
Kingsmore: With DRAGAN (Edico), 120GB down to 5.13MB variants. Problem of ref db's not tuned for variety of ethnicities #PMLS2016
12:20pm August 11th 2016 via Hootsuite
Kingsmore: Infant at 55d - coagulopathic. From consent to trio DNA ready to sequence, 6h. 24.5h: finished 30x WGS #PMLS2016
12:19pm August 11th 2016 via Hootsuite
Kingsmore: Credits ILMN and Edico with Rady. 800 biotech co's in SD; genomic literacy high in SD, can decode in 26h #PMLS2016
12:18pm August 11th 2016 via Hootsuite
Kingsmore: Genetics are simple. 'Cancer is tough tough tough.' 50y of infrastructure around genetic disease #PMLS2016
12:17pm August 11th 2016 via Hootsuite
Kingsmore: He believes NICU is the most promising for PM. 8K genetic diseases, affecting 3% of children, leading cause of death #PMLS2016
12:16pm August 11th 2016 via Hootsuite
Kingsmore: Primary focus is NICU/Pediatric ICU. 14% of US newborns are admitted to a NICU. #PMLS2016
12:15pm August 11th 2016 via Hootsuite
