Opt-in, Opt-out, & Patient Led Databases · 7 n es ng 5,000 e-esearch Clinical Trials Sale al Phase...

Duane Schulthess

Managing Director

Copyright Vital Transformation - CONFIDENTIAL

Opt-in, Opt-out,

& Patient Led Databases Better Patient Outcomes,

Faster and Cheaper

Researchers are:

Dr. Daniel Gassull Duane Schulthess

2 © Copyright Vital Transformation - 2014

12/11/2014 3 © Copyright Vital Transformation - 2014

Sponsors and Supporters of the project:

Assumptions & Limitations:

• The theoretical time impact of databases on identification and

sign-in has been discussed and presented to numerous clinical

trial managers and researchers; these times are theoretical as

well as untested, and should be seen as goals or targets

• We assume the use of patient databases in Europe is

unaffected by the data protection legislation passed in the

European Parliament in March of 2014

• The ROI & Cost assumptions are based on averages across

therapeutic areas; our model is illustrative of relative, not

specific, value

• We assume there are many searchable health databases

operational in numerous international locations, this may not

be the case


The Problem

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Clinical Trials

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Phase 1 Phase 2 Phase 3

5,000

10,000

Compounds

250

Compounds

3 – 6 Years 6 – 7 Years

5

Therapies

1

Therapy

2 – 5 Years

Number of Patients/Subjects

20-100 100-500 1000-5000

Regulatory Review

Drug Discovery

Pre Clinical Testing

PhV

Monitoring

Total Cost: ~$2 Billion USD

Sources: Drug Discovery and Development: Understanding the R&D Process, www.innovation.org;

CBO, Research and Development in the Pharmaceutical Industry, 2006;

Forbes, Matthew Herper, “The Truly Staggering Cost Of Inventing New Drugs”, February 10, 2012

Current EU trial pathways are expensive and slow

New EU therapies don’t reach

patients until here

http://www.innovation.org/

http://www.forbes.com/sites/matthewherper/

http://www.forbes.com/sites/matthewherper/

Real World Evidence - Health Databases

8

Time of recruitment represents about 30% of total CT Time - roughly 30 months of development

Months

0.0

5.0

10.0

15.0

20.0

25.0

30.0

35.0

Start-up Recruitment Time Trial Time Data Clean-up & Report

Phase 3

Phase 2

Phase 1

30% of Clinical trial 30 months in total


Source: CMR International. Pharmaceutical R&D Factbook 2011, Thomsom Reuters, May 2011

Current development times by clinical area

(1) Target indications of the project FDIH = First-dose in Humans, here considered before Phase 1 Source: CMR International. Pharmaceutical R&D Factbook 2011, Thomsom Reuters, May 2011

0 1 2 3 4 5 6 7 8 9 10

New Chemical entity

New Biological Entity Toxicity to FDIH

Phase 1

Phase 2

Phase 3

Submission

Years

0 1 2 3 4 5 6 7 8 9 10

Cardiovascular

Anti-Cancer

Central Nervous System

Toxicity to FDIH

Phase 1

Phase 2

Phase 3

Submission

Years


Three queries from clinicaltrials.gov were selected to test databases Alzheimer’s Disease

Cardiovascular disease

Inclusion criteria Male and Female > 18 years Diagnosis of NSCLC Stage IIIB not amenable to curative treatment or Stage IV. No prior chemotherapy for lung cancer. Patients must have at least one uni-dimensionally measurable lesion. Prior radiation therapy to less than 25% of bone marrow, whole pelvis not allowed. Radiation must be completed at least 4 weeks prior to study enrollment.

Exclusion Criteria: Treatment with any drug within the last 30 days that has not received regulatory approval. Serious cardiac condition. Serious medical disorder in addition to NSCLC that would make it difficult for the patient to complete the study. Inability or unwillingness to take folic acid or Vitamin B12 supplementation. Presence of fluid retention that cannot be controlled by drainage.

Inclusion Criteria Male and Female >50 Probable or possible Alzheimer's disease Living in skilled nursing home Exclusion Criteria Other types of dementia, psychiatric or neurologic disorders Musculoskeletal disease

Inclusion Criteria Male and Female >18 years Must be on background lipid lowering treatment. Must be at high risk of a CV event. Must have an LDL C >/=70 mg/dL (1.8 mmol/L) and < 100 mg/dL (2.6 mmol/L) or OR, Must have non-HDL-C >/= 100 mg/dL (2.6 mmol/L) and < 130 mg/dL (3.4 mmol/L)

Exclusion Criteria An LDL C < 70 mg/dL (1.8 mmol/L) or >/= 100 mg/dL (2.6 mmol/L) or non HDL-C < 100 mg/dL (2.6 mmol/L) or >/=130 mg/dL (3.4 mmol/L) Planned coronary (PCI or CABG) or other arterial revascularization. New York Heart Association Class IV congestive heart failure or left ventricular ejection fraction < 25% by cardiac imaging. Chronic renal insufficiency with creatinine clearance of <30 ml/min/1.73m^2 by MDRD formula or with end state renal disease on dialysis. History of hemorrhagic stroke.

Non-Small Cell Lung Cancer

We studied these queries in three data systems that can be classified into two groups

Region # Patients in

Database Healthcare

setting Year created

Databases with electronic patient records*

CPRD – TrialViz UK 4.6 M GPs 2012

Penn Medicine – Oracle Health Science Network US 2.25 M Hospitals 2013

Databases led by patients(*)

Patients-Know-Best UK 150k Hospitals 2012

* Data is Anonymised/De-identified

Results CPRD – Trial Viz

Alzheimer disease: Result of Query with CPRD

Geographical Distribution of Hits Distribution of # of patients per practice

# of patients per practice

Inclusion Criteria

Male and Female >50

Probable or possible Alzheimer's disease

Living in skilled nursing home

Exclusion Criteria

Other types of dementia, psychiatric or neurologic disorders

Musculoskeletal disease

Number of Patients identified: 1,353

Query results – Anonymised Data

Alzheimer’s CPRD Penn

Medicine

Patients identified in query 1,343 890

Acceptance Rate Based on Historical Averages 60% (1,2) 60% (1,2) Total Patients Needed in

in Clinical Trials.gov

Total Potential Patient Trial Pool 670 445 249 (3)

(1) Avalon L. Am J Geriatr Psychiatry. 2009 Jan;17(1):65-74 (2) Fouad MN. et al. J Oncol Pract. 2013 Mar;9(2):e40-7 (3) Number of patients needed in entire trial (world wide) (4) Number of trial sites used in the actual trial

(*) Data shown in previous slide

11 (*) 1 53 (4)

Total Trial Locations Registered

in Clinical Trials.Gov

Total Implied Locations Required using revised

Data Base Search

Result of Query with CPRD: Cardiovascular Disease

Geographical Distribution of Hits Distribution of # of patients per practice

Inclusion Criteria Male and Female >18 years

Must be on background lipid lowering treatment. Must be at high risk of a CV event. Must have an LDL C >/=70 mg/dL (1.8 mmol/L) and < 100 mg/dL (2.6 mmol/L) or OR, Must have non-HDL-C >/= 100 mg/dL (2.6 mmol/L) and < 130 mg/dL (3.4 mmol/L).

Exclusion Criteria An LDL C < 70 mg/dL (1.8 mmol/L) or >/= 100 mg/dL (2.6 mmol/L) or non HDL-C < 100 mg/dL (2.6 mmol/L) or >/=130 mg/dL (3.4 mmol/L) Planned coronary (PCI or CABG) or other arterial revascularization. New York Heart Association Class IV congestive heart failure or left ventricular ejection fraction < 25% by cardiac imaging. Chronic renal insufficiency with creatinine clearance of <30 ml/min/1.73m^2 by MDRD formula or with end state renal disease on dialysis. History of hemorrhagic stroke.

Number of Patients identified: 136,053

© Copyright Vital Transformation - 2014

Query Results – Anonymised Data

Cardiovascular CPRD Penn

Medicine

Patients identified in query 136,065 982

Total Patients Needed in Clinical Trials.gov Acceptance Rate 10% (1) 10% (1)

Total Patient Trial Pool 13,065 98 650 (2)

(1) Harper D. B. ”Projecting realistic enrolment rates”. Monitor, Winter 2004, pages 15-18 (2) The clinical trial included 12,000 patients world-wide. Based on the number of hospitals in the UK and the rest of the world, 650 patients were

allocated in the UK (3) The clinical trial required and registered 461 trial locations. Assuming the acceptance rate to be the same world-wide, 24 locations were allocated

in UK


7(*) 7 (**) 24 (3)


Data Base Search



(*) Data shown in previous slide, (**) Number extrapolated, assuming all locations have ths same number of patients (i.e. 98)

Query Results – Anonymised Data

(1) Harper D. B. ”Projecting realistic enrolment rates”. Monitor, Winter 2004, pages 15-18 (2) The clinical trial included 12,000 patients world-wide. Based on the number of hospitals in the UK and the rest of the world, 650 patients were

allocated in the UK (3) The clinical trial required and registered 461 trial locations. Assuming the acceptance rate to be the same world-wide, 24 locations were allocated

in UK


Why is there a difference of two orders of magnitude between CPRD and Penn Medicine?

CPRD is GP data, Penn Medicine is hospital/outpatient/pharmacy data

Very few CVD patients go to the hospital every two years

(*) Data shown in previous slide

CPRD and Penn Medicine differ in population base, offering a different number of patients and depth of information

Patients with Lipid Lowering Treatment

Patients with LDL > 1.8 & <2.6

Patients without Renal Failure OR stroke

Patients without CABG or PCI

CPRD (5M patients)

Penn Medicine

(2.3M Patients)

CPRD captures general population Penn Medicine captures patients

CPRD offers a broad patient set, but without hospital data UPenn offers a narrow patient set with precise hospital data

Included patients Excluded patients


(*) All data obtained ar UPenn and CPRD was de-identified

Query results – Anonymised Data

(1) Madsen L.T. et al. J Natl Compr Canc Netw. 2014 Jul;12(7):993-8,

(2) Pauporte. I. J Clin Oncol 31, 2013 (3) World-wide values

Non-Small Cell Lung Cancer CPRD Penn

Medicine

Patients identified in query 0 262

Acceptance Rate 45% (1,2) 45% (1,2) Total Patients Needed in Clinical Trials.gov

Total Patient Trial Pool 0 118 1,713 (3)


N/A 15 134 (3)


Data Base Search



Patient Led Databases

20


• Survey was ran in partnership with two practitioners currently using the Patients Know Best platform

• Number of patients invited to participate in survey: 540

• Number of patients who took survey, 161

• Survey run in Fall 2014

• Confidence 95%, Margin= ± 5 % (80/20)

Survey


Yes 83%

No 17%

Do you or a member of your family have a chronic condition for which there is

currently no therapy or cure?


Yes 92%

No 8%

Would you be willing to share your medical health records (data) to help researchers find

needed new therapies and cures?


Yes 73%

No 27%

Would you be willing to participate as a research subject by taking new therapies to see if they work?


Patient-led databases can deliver a targeted result in specific disease areas

Population Men & Women >50 with risk of

Alzheimer’s

Final after inclusions and

exclusions

Acceptance Rate

Total Patients

Current CPRD 4.6 million 14,872 1,343 60% 670

Current Penn Medicine 2.25 million 4,549 890 60% 534

Theoretical Patient-Led Model in Alzheimer's

3,783 341 73% 249 (*)

(*) Number of patients needed in test Alzheimer trial = 249 Assumption: Patient-led database captures a population identical to (1) CPRD and (2) Penn Medicine

Impact on Time Needed to Bring

New Medicines to Patients


Databases can reduce time of indentifying a patient

Current recruitment (Phase 3)

9 months 3 months

Identification Sign-in

Recruitment with Database X months 3 months

Identification Sign-in

Total Time Saved


Impact of faster identification on R&D time of patients receiving cardiovascular medicines

Current 25% Reduction 50% Reduction 100% Reduction

Phase 1 (yrs) 1.8 1.8 1.8 1.8

Phase 2 (yrs) 3.3 3.1 3.0 2.6

Phase 3 (yrs) 3.1 2.9 2.8 2.4

Total (yrs) 8.2 7.9 7.5 6.8


Time

(years)

Phase 3

Phase 2

Phase 1

Industry Average R&D times for Cardiovascular drugs

Comment: “Reduction” means reduction of identification time

Impact of faster identification on R&D time of patients receiving Cancer drugs


Phase 1 (yrs) 2.4 2.4 2.4 2.4

Phase 2 (yrs) 3.3 3.1 3.0 2.6

Phase 3 (yrs) 3.1 2.9 2.8 2.4

Total (yrs) 7.4 7.0 6.8 6.0


Time

(years)

Industry Average R&D times for Cancer drugs


Phase 3

Phase 2

Phase 1

Impact of faster identification on R&D time of patients receiving Alzheimer drugs


Phase 1 (yrs) 1.8 1.8 1.8 1.8

Phase 2 (yrs) 2.7 2.5 2.4 2.0

Phase 3 (yrs) 2.7 2.5 2.4 2.0

Total (yrs) 7.2 6.8 6.6 5.8


Time

(years)

Industry Average R&D times for Alzheimer drugs


Phase 3

Phase 2

Phase 1

ROI for Saving Time – Calculating the Value


Patient databases significantly impact the business case of a drug

Reduces R&D time

Reduces number of recruitment sites

Reduces costs of Recruitment Process

Reduces Cost of Capital

Adds Sales (longer time in the market under patent protection)

Comment: This presentation does not consider reduction of recruitment costs (B), due to lack of consistent data.

Patient Databases

The impact of time on Cost of Capital: an example

Investor puts 10 M$

Annual rate of return: 10% Investor requires 20M$

7 years

5 years

Investor requires 16 M$ Investor puts 10 M$

Annual rate of return: 10%

By cutting time,

you save

4 M$

in cost of capital

R&D Project A

R&D Project B

5 years

Investor requires 32 M$ Investor puts 10 M$

Annual rate of return: 10%

Project B with failure rate of 50%

BUT,… Investors also consider risk of failure

Failures raise the average development cost of a marketed drug from 215M$ to 0.9-2.3b$

Phase 1 Phase 2 Phase 3 CT Cost per

Drug

Average Cash (Direct) Cost of Clinical R&D (a) 16 M$ 42 M$ 158 M$ 215 M$ (1)

(1) Cost per drug approved, industry average (2) Cost of Capital = 11% (3) Current time to market from slide 28-30

Probability of Success (b)

CT Cost of Marketed Drug (2,3)

Cardiovascular 13% 24% 74% 1,025 M$

Anti-Cancer 17% 26% 62% 880 M$ (c)

Central Nervous System 5% 9% 33% 2.365 M$

(a) Paul, S.M. et al. (2010), Nature Reviews Drug Discovery. 9(3), 203-214 (b) CMR International. Pharmaceutical R&D Factbook 2011, Thomsom Reuters, May 2011 (c) Cancer drugs are substantially more expensive to develop than $215 mil, and have a higher

success rate due to programmes such as conditional approval due to unmet medical need.


Estimated impact for cost of capital in CVD


Current Reduction 25% Reduction 50% Reduction 100%

Phase 1 (yrs) 1.8 1.8 1.8 1.8

Phase 2 (yrs) 3.3 3.1 3.0 2.6

Phase 3 (yrs) 3.1 2.9 2.8 2.4

Total time (yrs) 8.2 7.9 7.5 6.8

Time saved (months) - 3.6 8.4 16.8

Cost of R&D 1,025 M$ 995 M$ 965 M$ 910 M$

R&D Savings - 30 M$ 60 M$ 115 M$

(1) Success rates are included in these calculations (2) Including cost of capital: 11%

Estimated impact for cost of capital in Cancer drugs



Phase 1 (yrs) 2.4 2.4 2.4 2.4

Phase 2 (yrs) 2.8 2.6 2.5 2.1

Phase 3 (yrs) 2.2 2.0 1.9 1.5

Total (yrs) 7.4 7.0 6.8 6.0

Time Saved (months) - 4.8 7.2 16.8

Cost of R&D 880 M$ 855 M$ 830 M$ 785 M$

R&D Savings - 25 M$ 50 M$ 95 M$


Estimated impact for cost of capital in Alzheimer’s




Phase 1 (yrs) 1.8 1.8 1.8 1.8

Phase 2 (yrs) 2.7 2.5 2.4 2.0

Phase 3 (yrs) 2.7 2.5 2.4 2.0

Total (yrs) 7.2 6.8 6.6 5.8

Time saved (months) - 4.8 7.2 16.8

Cost of R&D 2,365 M$ 2,295 M$ 2,225 M$ 2,095 M$

R&D Savings - 70 M$ 140 M$ 270 M$

Saving time reduces cost of capital by 4-10% per phase of clinical trial costs (*)


Savings in Cost of Capital

(as % of R&D spending per trial)

Expected time saved

with Databases

Comment 1: Average time of conducting CT differs by phases, so does cost-of-capital (*) Savings of Cost of Capital computed when the drug is NDA ready

0%

4%

8%

12%

16%

0 2 4 6 8 10 12

Phase 3

Phase 2

Time Saved

(Months)

Savings in cost-of-capital are driven by identification time


Variable Range Variation about

centre value Centre value

Reduction of Identification time 25 – 75% ± 50% 50%

Sign-in time 4.5 – 1.5 months ± 50% 3 months

WACC 9 – 13% ± 2% points 11%

Average cost of Phase 1 trial per drug 8 – 24 M$ ± 50% 16 M$



60 M$ 70 M$ 80 M$ 90 M$ 50 M$ 40 M$ 30 M$

Savings of Cost of Capital in industry-wide R&D spending per marketed drug (Cardiovascular case)

Identification time

Sign-up time

WACC

Cost of Phase 1

Cost of Phase 2

Cost of Phase 3

MAPPs and Real World Patient Databases


NRDD vol. 10, July 2011

Initial narrow license,

small targeted

population with clear

bio-marker

Progressively include larger populations including

marker negative

Medicines Adaptive Pathways to Patients (MAPPS)

Managing uncertainty:

1. Starts by targeting the most likely to respond

2. All key stakeholders (patients, regulators, practitioners, industry) are aligned with the process starting at the design stage

3. Robust capture of real-time data of the actual trial experience

Conclusions



1. Real World Evidence from GP, hospital and patient-led databases has the potential to reduce the time to bring needed new medicines to patients.

2. The strategy of database development should combine Hospital Data, GP Data, and Patient Led datasets; this provides the greatest flexibility and depth of data.

3. Patient Databases can support the evolving data required in support of MAPPs pathways to develop a more efficient approval process

4. The data sharing draft legislation passed by the European Parliament in March of 2014 puts at risk the use of Anonymised national patient databases in the EU; R&D will follow the path of least resistance

Duane Schulthess Managing Director

www.vitaltransformation.com

Copyright Vital Transformation - CONFIDENTIAL

QUESTIONS?

http://www.vitaltransformation.com/

Appendix


The full development of a drug for heart diseases costed about 3b$, while for obesity and diabetes 150-300 M$


Average cost of developing one drug for… (1,2) Phase 1 Phase 2 Phase 3 Total

Obesity 2.3 M$ 22 M$ 253 M$ 277 M$

Diabetes 0.6 M$ 13 M$ 143 M$ 157 M$

Heart Disease 1.8 M$ 172 M$ 2,854 M$ 3,028 M$

(1) Roy A.S. Stifling new cures: the true cost of lengthy clinical drug trials. Project FDA report, Manhattan Institute for Policy Research No5 (2012) (http://www.manhattan-institute.org/pdf/fda_05.pdf)

(2) Excluding failure rates

http://www.manhattan-institute.org/pdf/fda_05.pdf



Cost of developing a drug for heart diseases is about 10X that of developing drugs for other cardiovascular diseases


Obesity Phase 1 Phase 2 Phase 3 Total

Lorquess 2.3 M$ 38 M$ 368 M$ 408 M$

Qnexa - M$ 7 M$ 177 M$ 184 M$

Contrave - M$ 23 M$ 214 M$ 237 M$

Diabetes

Byetta 1.1 M$ 9 M$ 68 M$ 78 M$

Bydureon 0.4 M$ 4 M$ 152 M$ 156 M$

Victoza 0.4 M$ 27 M$ 210 M$ 237 M$

Heart Disease

Xarelto 1.1 M$ 207 M$ 2,866 M$ 3,074 M$

Eliquis 2.5 M$ 137 M$ 2,842 M$ 2,981 M$

(1) Roy A.S. Stifling new cures: the true cost of lengthy clinical drug trials. Project FDA report, Manhattan Institute for Policy Research No5 (2012) (http://www.manhattan-institute.org/pdf/fda_05.pdf) (2) Excluding failure rates




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