Crowdsourcing Patient Inclusion/ Exclusion Criteria

Crowdsourcing patient inclusion/ exclusion criteriaStatistically relevant trials with fewer patients

Confidential. Copyright 2015 2

We help pharmaceuticals address two specific challenges

Challenge

CAX Solution

When

Minimize Patient Enrollments Revive ‘Failed’ Trials

Many clinical trials fail to enroll the required # of patients on time

Trials that fail due to unmet efficacy end points are hard to recover from and can be devastating

Identify minimal number of patients needed for a statistically relevant trial; reducing no. of patients to be tested by 20-30%

Identify sub-group of patients that meet efficacy end points and define patient inclusion/ exclusion criteria for a trial targeted at the selected sub-group

Typically, post Phase II Success Typically, post Phase III Failure

CAX Unique Approach Hundreds of machine learning and statistical algorithms are compared to arrive at the most accurate patient selection criteria

Confidential. Copyright 2015

How it works


• Client provides de-identified clinical trial data from Phase II/ Phase III trials

• Includes demographic, genetic, clinical, imaging and other biomarker data

• CAX further transforms the data to remove context before sharing with the Solver community

Data TransformationAnalysis Validation Inclusion/Exclusion Criteria

1 week 4 weeks 1 week 1 week

Data Transformation


• CAX defines competition to score patients based on their response to a drug

• 300+ Solvers submit 1000+ independent predictive models to score patients and identify the most important patient characteristics

• The top 10 models are selected based on their prediction accuracy

Data Transformation Analysis Validation Inclusion/Exclusion Criteria

1 week 4 weeks 1 week

Analysis

1 week


• Heat map of the top 10 models is created

• Business sanity checks are done to further narrow the models

• Results are compared to minimize the statistical variance and improve the reliability of the outcomes



Validation

1 week


• Outcome of the top models are used to develop a simplified decision tree

• Decision tree paths are labeled as inclusion or exclusion criteria



Inclusion/ Exclusion Criteria

1 week


Compared to traditional analytics, CAX approach is significantly better

Accuracy

Reliability(rigor employed to solve your

problem)

Time(time to deliver value)

Capacity

• Matching current parameters

• Single approach to a problem

• Matching current parameters

Our solvers often exceed accuracy levels in published journals

• Multiple approaches to the same problem

Hundreds of different approaches result in statistically more robust results, especially in cases with limited data efficacy data available from Phase II trials

• 6 weeks• 15-20 weeks

• On-demand

>90% of projects completed with 6 weeks. Traditional analytics teams often take this time to “mobilize resources”

• Allocated by project

Cost• Outcome based

Payment based on achievement of milestones

• FTE / Hour model

Traditional Analytics’ Approach CAX Approach


A case study

A top 5 pharma needed help in configuring patient selection criteria for more optimized execution of Phase III clinical trials


1232

As a recent example, the CAX platform was used to predict which patients are likely to have an exacerbation, so that client can select similar patients for future trials

~3,000 model submissions received

Top 20 solver Stats1,232 SubmissionsAUC: 0.8 – 0.85

>=25%

>=50%

>=70%

>80%

All

8

3

3

2

5

Input Data Crowdsourced Analytics Process Outcomes

# of top 20 models that predicted all or some of the top patient selection criteria

For the top models: Prediction Accuracy is typically ~5-20% better than client’s algorithms.

1300 attributes of 6000 patients:

- Genetic attributes- Clinical measurement

attributes- Patient demographics

attributes


CrowdANALYTIX approach achieved 20% reduction in cost and time in comparison to client benchmarks

Effective results delivered through on-demand capacity in under 35 days

• Over ~3,000 Model Submissions including code from the Top solvers

• List of Top biomarkers identified to screen patients ranking 1,300+ patient attributes (including genetic biomarkers)

• Patient inclusion/ exclusion criteria

• 20% reduction in clinical trial costs

• 400+ Solvers participating in the problem

• AUC (Accuracy level) of Top Solvers in the range of 0.8 – 0.85 (better than published algorithms)

• Model delivered to client in 35 days

• Contest duration of 26 days

Key Deliverables

Participation & Outcomes

Duration

For recent case example


About usCrowdANALYTIX is a crowd-sourced analytics service for pharmaceutical firms and CROs. CrowdANALYTIX gets hundreds of data scientists to independently analyze trial data to define inclusion/exclusion criteria


A diverse community of data experts

50+ 70%7500

+50+Countries

70%PhDs, Masters

7500+

Data Experts


Who have we worked with: Life Sciences, Professional Services

“One of the greatest advantage of the crowdsourcing approach was that there was available talent ready to work on my problem. I can almost guarantee that the crowdsourcing approach dedicated significant more man-hours on this project than I would ever been able to get through internal resources.”

Principal Research Scientist at a Major Pharma company

“The fresh perspective from one of the analysts triggered a key insight that had eluded us”

Ashish Kelkar, Director – Infrastructure Strategy & Analytics, Facebook


1999 S Bascom Ave, Suite #700Campbell, CA - 95008

866.333.4515

facebook.com/crowdanalytix

@crowdanalytix_q

[email protected] [email protected]

Crowdsourcing Patient Inclusion/ Exclusion Criteria

Healthcare

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