Cancer Trials in IndiaPosited Challenges and Required Skills

Dr. Bhaswat S ChakrabortySr. VP, R&D, Cadila Pharmaceuticals

Ltd.

Contents• Global Cancer Clinical Trials

• General challenges in design, conduct, analysis and interpretation of cancer CTs

• Cancer CTs currently being conducted in India

• Challenges specific to India– Funding of trials in India

– “Learn by hearing and doing” culture• Lack of training in good documentation and reporting

– Perceptions about clinical trials in India

– Uneven expertise

– Following international templates

– Lack of databases that would facilitate• Centre capacities and strength, recruitment rate and historical data

– Lack of recognition

– Evolving regulatory framework

• Some solutions

Global Cancer Trials

Cancer Trials (Phases I–IV)• Highly complex trials involving cytotoxic drugs, moribund patients,

time dependent and censored variables

• Require prolonged observation of each patient

• Expensive, long term and resource intensive trials

• Heterogeneous patients at various stages of the disease

• Prognostic factors of non-metastasized and metastasized diseases are different

• Adverse reactions are usually serious and frequently include death

• Ethical concerns are numerous and very serious

• Trial management is difficult and patient recruitment extremely challenging

• Number of stopped trials (by DSMB or FDA) is very high

• Data analysis and interpretation are very difficult by any standard

• more………

100

1080

2060

3040

4020

5000

0.8 0.9 1.0 1.1 1.2 1.3 1.4 1.5 1.6

Relative risk

6

8

10

12

16

24

48

60

72

m1

Sample Size at Different Rates of Death

Alpha=0.5; Power =0.9; Accrual = 6 months; Follow up = 24 months

m1 is the median survival time on control arm

Accrual Time and Sample Size

200

760

1320

1880

2440

3000

0.80 0.85 0.90 0.95 1.00 1.05 1.10 1.15 1.20

Relative risk

6

7

8

10

12

A

Accrual Time has very Little Effect on Sample Size!!

Alpha=0.5; Power =0.9; Accrual = 6 months; Follow up = 24 months

Follow Up Time and Sample Size

200

760

1320

1880

2440

3000

0.80 0.85 0.90 0.95 1.00 1.05 1.10 1.15 1.20

Relative risk

6

8

10

12

16

24

48

72

120

F

Alpha=0.5; Power =0.9; Accrual = 6 months; median control survival time=10 months

Ratio of Number of Patients in Control vs Test and N

200

760

1320

1880

2440

3000

0.80 0.85 0.90 0.95 1.00 1.05 1.10 1.15 1.20

Relative risk

0.5

0.6

0.8

1

1.2

1.4

1.8

2

5

m

Alpha=0.5; Power =0.9; Accrual = 6 months; Follow up = 24 months

m is the ratio of number of patients in control arm to experimental arm

Loss of Power if N for Control arm is Very Low

200

760

1320

1880

2440

3000

0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0

Power

0.5

0.6

0.7

0.8

1

2

3

0.2

m

Power vs Detectable Alternativefor Small Trials

0

0.2

0.4

0.6

0.8

1

0 10 20 30 40 50 60

Detectable alternative

10

12

16

24

36

48

m1

Alpha=0.5; Median Control Survival Time = 10 months; Accrual = 6 months; Follow up = 24 months; small sample size, e.g. 50-100

Sample Size vs Detectable Alternativefor Small Trials

Alpha=0.5; Median Control Survival Time = 10 months; Accrual = 6 months; Follow up = 24 months; small sample size, e.g. 50-100

50

80

110

140

170

200

0 10 20 30 40 50 60

Detectable alternative

10

12

16

24

36

48

m1

Power vs Detectable Alternativefor Large Trials

Alpha=0.5; Median Control Survival Time = 10 months; Accrual = 6 months; Follow up = 24 months; Large sample size, e.g. N≥1000

0

0.2

0.4

0.6

0.8

1

0 10 20 30 40 50 60

Detectable alternative

10

12

16

24

36

48

m1

Bad or Wrong Methods of Analysis• Comparison of life tables at one point in time ignoring their structure

elsewhere (except very rapid processes)

• If a few patients are at risk for more than a certain time but do not die, this should not be taken as evidence of cure. Look at all the data of all the patients

• Median survival times are not very reliable unless the death rate around that median is very high

• A simple count of number of death in each group is inefficient as it ignores the rate of death

• The best estimate of the probability of survival for a certain time (say 5 years), is given by the life table value at that time. Other simplistic calculations may be misleading

• Randomized controls are always better than historical controls

Bad or Wrong Methods of Analysis contd.

• Estimation of survival is best done from randomization time. If it is done from the time of 1st treatment it can be misleading (as initiating time for two treatments can be different)

• Superficial comparison of the slopes of survival graphs as it biases the proportion surviving at each given time

• Declaring ITT is better than per protocol analysis or the reverse

– Check all the data carefully especially the P values associated with either type of analysis

• When you get an overall non-significant treatment effect, do not insist that a sub-stratum can still benefit from the treatment even if that stratum analysis is significant

• Realistically not checking the actual number of survivors on the last day of the study (follow up)

• Be sure of your reason to use and report one-sided vs. two-sided t-tests

Total 256

Total 48 Trials

Total 155

Total 30

Funding of Trials in India - Projection

Source: IndiPharm projections based on information from The Boston Consulting Group and Business Communications Co.

Funding of Indian Trials - Observations

• Majority of (part of) international trials in India are well funded

• Indian Govt. sponsored trials are also well funded

• This has contributed to– Infrastucture of hospital and clinic-based research centres

– GCP training

– Institution of formal IRBs

– Better CRF filling and record keeping

• Some international and most national sponsors are still aggressive “bargain-hunters”

• Perception of different qualities of trail design and data generation for national and international Regulatory agencies

• Despite Sch. Y, non-harmonization in standards will be a huge burden for future

Research Culture: Traditional vs Participative

• Traditional– Auditory instructions are followed better than written instructions

– Strong reflection abilities (than theorising and experimenting)

– Doing while learning, service oriented

– Record keeping and documentation are not always good

– Participation, discussion and questions are not encouraged highly

– Teachers and trainers are considered authorities

• Participative– Open, friendly and novelty oriented

– Consensus oriented

– Theorising , hypothesising and experimentation encouraged

– Documentation is highly encouraged

– Trainers/teachers are friends and helpers

Perceptions about Clinical Trials in India

Regulatory Framework

• Evolving, much better than what was 5 years ago

• The DCGI approval process– Type A clinical trials (protocol approved by developed regulatory authority

e.g., U.S., Canada, U.K., Switzerland, Germany, Australia, Japan, and South Africa); 4-6 weeks

– Type B trails are the rest; 8-12 weeks

• IRB approval and import licenses can be had in parallel with DCGI review

• However, DCGI is still understaffed and domain specialists are very few

• DCGI still has unique standards and precedence (e.g., acceptance of single arm CT as key evidence of S&E) which need to be harmonized with international standards

Other Challenges Specific Indian Oncology Researchers

• Training in design concepts and nuances

• International design templates but Local conditions– Late reporting stage

– Unpredictable and uncharacterized social influences

– Informed consent may not be “free-willing”

– High levels of consent withdrawal

– Lack of Databases to estimate population baselines, population effect size and variability for the standard (control)

Challenges Specific Indian Oncology Researchers

• Unpredictable recruitment rate– Rural patients

– Poor and uninformed patients

– Inadequate counseling

• Varying expertise– Competence

– Training

– Institutional support

– Lack of or improper understanding of responsibility and liability

– Inadequate DMCs

• Lack of recognition– As leading trialists

– Low impact Indian journals in the pertinent areas– Many inconveniences of regional centres and publicly funded institutions

Solutions• Understanding and accepting the gaps

• Participation in international co-operative trials

• Extensive training– Research methods

– Trial design

– Ethics

– Documentation skills

– Validation skills

– DMC

– Data analysis and interpretation

• Investigator and Site Development– Not only sponsored by Pharma companies but also organised and

invested by Govt.

– Structured programs in universities and institutes

Solutions…

• Curriculum development

• People and domain networking

• Publications– In high impact journals

– Strategizing improvement of Indian journals

• Conferences and other common forum– Like this one

• Govt.-academia-industry ventures and (noble) incentivization

• Encouraging creativity and higher education

• ……………

Thank You Very Much