Best Practices for Probiotic Clinical Research · Clinical Research Regulations – Dietary...

Best Practices for Probiotic

Clinical Research

Clinical Research Regulations – Dietary Supplements/NHPs

www.nutrasource.ca © Nutrasource Pharmaceutical and Nutraceutical Services 2019

US – Dietary Supplement� Code of Federal Regulations (CFR)

� Part 50 – PROTECTION OF HUMAN SUBJECTS

� Part 56—INSTITUTIONAL REVIEW BOARDS

Both are applicable to dietary supplements as stated in the scope detailed in the CFR.

FTC case law defines “competent and reliable” scientific evidence in only general terms as: “tests, analyses, research, studies, or other evidence based on the expertise of professionals in the relevant area, that have been conducted and evaluated in an objective manner by persons qualified to do so, using procedures generally accepted in the profession to yield accurate and reliable results.”

Canada – Natural Health Products� Regulation: Part 4 of the Natural Health Products

Regulations (NHP Regulations) June 18, 2003 (SOR/2003-196)

� Section 74: “Every sponsor shall ensure that a clinical trial is conducted in accordance with good clinical practices”

� Guidance: Clinical Trials for Natural Health Products Guidance Document

Summary of the Principles of ICH

1. Conduct trials according to GCP

2. Weigh risks vs. benefits

3. Subjects wellbeing exceed scientific needs

4. Have adequate information to justify trial

5. Write a sound protocol

6. Receive IRB approval

7. Use qualified physicians

8. Use qualified, trained (education and experience) staff

9. Obtain informed consent

10. Record all information appropriately

11. Confidentiality & data protection

12. Handle IP appropriately (GMP, use per protocol)

13. Quality Assurance


ICH Ancillary Guidance Documents


Why GCP? Regulatory Acceptability


Clinical Trial Design & Infrastructure

IND/Biologic Clinical

Investigations

(Global Application)

Natural Health Products

(Canada) / Global

Application

ICH E6 (R2)

(Global)

NHPR / ICH

(Canadian Regulation)

Unregulated

?

Dietary Supplements

(US Application)

Validation

Documentation

Inspection

Readiness


Claims Substantiation

Validation

Documentation

Risk


Regulatory Insight

• Deficiencies in studies submitted to substantiate claims to EFSA (adapted from Guidance on Statistical Reporting EFSA Journal 2014; 12(2):3908)

• Inappropriate patient population or inclusion/exclusion criteria

• No or lack of control group

• Inappropriate statistical powering of study

• Insufficient method of randomization

• Inappropriate statistical tests and reporting of results


Best Practices – Study Participants (Target Population)

• Define the target population• General population?

• Subset of population?

• Jurisdiction of interest?

Study Design Challenges:

• Use of enriched populations

• Combining product efficacy with microbiome analysis / genetics to identify potential responders -> reduce sample size and potential success rate


Best Practices – Study Product / Control and Blinding

• Choice of Control Groups

• Placebo?

• Active Comparator?

• Standard of Care?

• Ensure:

� All groups get the same number, types of product,

and dose regimen

� If capsule/tablet, ensure all have similar

characteristics (size, weight, color, no unique

markings, etc.)

� If food (e.g. yogurt) choose an acidified milk with

no active cultures, or heat-treat the yogurt

� The protocol should include the justification for

choice of control product and measures to ensure

blinding


Best Practices – Blinding (Example 1 – Dose Finding Trial)

Groups

Group 1 Group 2 Group 3 Group 4

Products Low-Dose Mid-Dose High-Dose Placebo

Active

Capsules1 2 3 0

Placebo

Capsules2 1 0 3

Total Capsules

/ day3 3 3 3


Best Practices – Blinding (Example 2 –Comparator Trial)

Group

Group 1

(Test Product

(capsule))

Group 2

(Comparator

Product

(yogurt))

Group 3

(Placebo)

Pro

du

ct

Active Capsule �

Active Yogurt�

Heat-Treated Yogurt � �

Placebo Capsule � �


Best Practices – Blinding (Product Packaging)

Labels:

� Must meet local and

federal requirements

� Should prevent any

accidental unblinding

� Should not differ except

by randomization

number


Randomization

• Eliminates the selection bias

• Balances the groups with respect to many known and unknown confounding or prognostic variables

• Forms the basis for statistical tests

• Generating randomization tables needs to be reproducible

• Generation of a randomization schedule usually includes obtaining the random numbers and assigning random numbers to each subject.

• Best practice is to use computer programming to do randomization such as SAS

• Common Types of Randomization in Clinical Research• Simple randomization

• Block randomization

• Stratified randomization

• Covariate adaptive randomization


Sample Size

• Sample size should reflect:– Effect size (Mean change over and above placebo)

– Estimate of variability regarding the change (SD)

– Level of power (80%, 90%)

– Estimate attrition rate (withdrawals)

– Statistical significance (P value, e.g. 0.05 (5% the result is due to chance))

• Estimates should be made based on prior research on specific formulation– If information is unavailable, study may be considered

proof of concept study, may be suitable for guidance of future studies


Determining Effect Size and Dose

• Pilot study in target population, multiple doses, placebo-controlled

• Results provided from study design:

• Determination of effective dose

• Effect size

• Estimate of variability in response

• Measure of efficacy


Statistical Analysis Plan

• Should be available prior to data analysis (latest before database lock) (not ad hoc)

• Contains analyses and population definition including inclusion/exclusion criteria as well as subgroup analysis and their relation to the study objectives

• Potential issues should be anticipated, and response to manage such incidents documented


Product Characteristics - Stability

• Live organisms require specific handling and storage to maintain efficacy

• Stability testing is a risk mitigation strategy for clinical trials

• Regulatory bodies (such as Health Canada) require stability data to be

submitted to support probiotic clinical studies

– At minimum, to demonstrate stability of the product for study duration

– Conduct real-time studies with the clinical investigation, allowing substitution of a new

lot during trial if stability of product starts to drift


Product Characteristics - Stability

Complementing Real-time stability:

• Ship using a validated shipping container and include a digital data logger

• Include extra bottles (QC samples) in the shipment for testing viability at

defined periods during the trial (on receipt at CRO/site, specific time

points during study, on last subject last visit)

• Collect and test random subject returns to provide confidence that study

product was help appropriate by study subjects

• Depending on product-specific requirements, it may be necessary to

provide the CRO / site(s) with coolers for transport if the probiotic is

sensitive to heat exposure.


Product Characteristics – Duration of Intervention

The duration of intervention should be based on:

• The time it takes for the product to have an effect

• Duration should be long enough for transient effects to stabilize

• Consideration must also be given to the outcome of interest

• If crossover design, how long do the products effects last? Will the

markers of interest return to similar baseline levels, and if so, how long

does this take?


Sample Characteristics – Stability

• Defined in Protocol or ancillary documents such as a Laboratory Manual

• Preparation and storage of samples should be based on validated methodology

• Points of consideration:– Sample collection – temperature, time between sampling and processing and/or

storage, are buffers/preservatives needed?

– Blood collection – tube type (EDTA, K2EDTA, Sodium citrate, sodium fluoride, heparin)?

– Transfer tubes – is there binding to the plastics, is sterility needed?

– Processing – conditions for rotating or vortexing, centrifugation, transfer at room temperature / duration before storage

– Storage – room temperature, refrigerated, frozen (-20°C or -80°C)

– Stability – how long can samples be stored (stability assays on sample storage) for and analysis still valid? Freeze thaw cycles?


Confounding Factors

• Inclusion and exclusion criteria must be carefully and explicitly defined, considering factors such as:– Activity levels

– Dietary habits

– Concomitant medications (including supplements)

– Blood and urine markers

• Broad enough to include those effected by the claim, but exclude those who may experienced increased risk of safety associated with:– Product use

– Interactions with other drugs

– Other confounding factors which may influence the study


Endpoint Selection

• Formulated in correspondence with the claim, considering acceptable biomarkers and validated questionnaires

• Clearly defined and measured in clinical study to prevent misestimating sample size or failure of hypothesis


Endpoint Selection


Importance of Data Management

• Data management is like filing, do it well and you can find

answers quickly

• Increasingly important as regulators and industry continue to

push toward

• Real world data

• Wearable technology

• Virtual trials

• Novel trial designs

• Increased vigilance of safety data


Data Management

MD trial

MD trial

MD trial

Academic

trial

Academic

trial

Academic

trial

Sponsor

trial

Sponsor

trial

• How can the Sponsor

use all these data?

• Are there common themes emerging?

• Are there any safety issues?

• Do the Sponsor controlled trials support

findings in other non-Sponsor Initiated

Studies?


Data Management

Global Data Management Plan:

Standardize data elements in line with current and emerging standards

(clinical and non-clinical)

Aggregate Data by 1) Species or 2) Strain

Subset Data by Indication Subset Data by Indication

• Assess probiotic-drug interactions

• Assess probiotic-disease interactions

• Assess weight on evidence

• Assess total subject exposure


Data Management

Data standards for coding

- MedDRA, WhoDD

Data standards for research

(e.g. CDISC, CDASH)

Safety Profile by

Strain and by

Indication

Investigator

Brochure

ADR Reporting

RCTs, etc.

ICH RegionCTA, PLA, IND


Data Management

Data standards for coding

- MedDRA, WhoDD

Data standards for

research

Safety Profile by

Strain and by

Indication

Investigator

Brochure

ADR Reporting

RCTs, etc.

ICH RegionCTA, PLA, IND


Nutrasource Pharmaceutical and Nutraceutical Services

120 Research Lane, Suite 203Guelph, Ontario, Canada N1G 0B4

www.nutrasource.ca

Joshua Baisley, B.Sc.Vice President, Clinical Design & Delivery

[email protected]

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