Download 8. Patient Stratification

 Case Study
Patient stratification to enhance
clinical trial outcomes
Segment patient
population using
predictive analytics
CrowdANALYTIX community can help identify
specific prognostic indicators to segment patients
based on genomic profiles as well as predisposition
to respond favorably or adversely to treatment
The CAX
approach to
segmenting
patients to
improve chances
of a successful
clinical trial
Problem Context
For example, in clinical testing, small patient samples make it challenging to distinguish between disease resistance and unresponsiveness. Knowing this upfront can make a significant difference to the outcome of the trial. For instance, in the case of a cancer treatment, a patient’s unique genetic biomarkers may make the patient resistant to the drug or not respond well to treatment. If clinicians knew which patients are likely to be unresponsive, they can adjust the trial criteria to target a sub-­‐‑
group of patients that will benefit the most. 1
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How CrowdANALYTIX helps
1. Using their clinical data and genomic markers create predictions of how symptoms of patients likely would progress 2. This statistical analysis would enable discovery of prognostic biomarkers and other indicators for patient stratification across various criteria 3. This enables segmenting patients by their profiles as well as their predisposition to respond favorably or adversely to treatment. 4. For example, it may help researchers quickly identify specific indication sub-­‐‑types or sub-­‐‑
groups of patients that are likely to respond well to treatment and tailor clinical trials targeting patients with that particular profile. 5. Analyze patient subgroups to isolate responder characteristics and inform additional experiments and subsequent clinical trials. delivery of models to the client takes less than 6 weeks.
Impact
The CrowdANALYTIX output helps our Life Sciences clients in 3 key aspects: (1) Reduce time to drug approval (2) Increase clinical trial success rates and efficacy by prioritizing resources (3) Reduce complications from poorly targeted drugs. Using these analytics, the researchers can adjust their trial criteria with this information, potentially saving hundreds of millions of dollars in failed clinical trials while reducing the likelihood of harm to patients. Deliverables: Submissions from Solvers
• Model submissions: Solvers submit models to analyze the genetic information related to identify prognostic biomarkers and potential stratification criteria for patients • Top factors: The solvers used the clinical and genomic data provided for patient population to identify the top factors to segment the patient population aligned with client objectives The entire process from launching the contest to About CrowdANALYTIX
CrowdANALYTIX is a crowd-­‐‑sourced analytics service to support the growing need for analytics expertise in the Life Sciences and Professional Services industries. CrowdANALYTIX operates a crowd-­‐‑sourcing platform in which a large community of independent analytical experts solve your problems using a competitive contest model. A CrowdANALYTIX Solution Manager manages your project to completion. Visit us at www.crowdanalytix.com © Copyright 2015, CrowdANALYTIX. All rights reserved. No part of this document may be reproduced, stored in a retrieval system, transmitted in any form or by any means, electronic, mechanical, photocopying, recording, or otherwise, without the express written permission from CrowdANALYTIX. The information contained herein is subject to change without notice. All other trademarks mentioned herein are the property of their respective owners. 2