Risk-Based Sourcing for Bovine Materials in FDA-regulated Medical Products:

Introduction and General Considerations

FDA TSE Advisory Committee MeetingHoliday Inn

Silver Spring MD

12 February 2004

David M. Asher, MDLaboratory of Bacterial, Parasitic and Unconventional Agents

Division of Emerging & Transfusion-Transmitted Diseases

Office of Blood Research and Review

Center for Biologics Evaluation and Research

United States Food and Drug Administration

e-mail address: asher@cber.fda.gov

Risk-Based Sourcing for Bovine Materials in FDA-regulated Medical Products:

Introduction and General Considerations

Recent TSE-related events with implications for safety of FDA-regulated products Presumptive transfusion-transmitted vCJD Cow with BSE in Washington State

Human blood/tissues and related products Products containing or manufactured with

bovine materials Risk analysis and TSEs Existing safeguards (“firewalls”), enhancements Possible additional safeguards for injectable

biologics and similar products: discussion points

Risk Analysis for Products:Conventional Definition

Risk Assessment (Paradigm of Natl Acad Sci USA /Natl Res Council report 1983)

1. Identify hazard

2. Characterize hazard (dose-response)

3. Estimate probable exposure to hazard

4. Characterize risk (from estimated probable exposure and dose-response)

Risk Management (based on assessment)

Risk Communication

Risk Assessment for Products:General Elements

of Microbiological Risk

Source of raw materials (contamination)

Manufacturing process Reduction of contamination

(ability to inactivate or remove contaminant)

(? Concentration/increase of contaminating agent)

End-use (frequency, amounts, routes)

“Effective” Exposure to TSE Agent (Kimberlin):

An Exposure Sufficient to Infect a Recipient

Dose of agent (infectivity/volume x total volume) Route of exposure

(CNS>intravenous>im/subcut >> oral) Host susceptibility

Species barrier (variable, not absolute)

? Agent “virulence” (? BSE > scrapie)

Quantitative Risk Assessment

Expresses risk as an overall probability Tries to represent the complexity of real

situations as “scenarios” (called System or Fault Tree or Failure Modes-and-Effects Analysis: multiply individual probabilities of a series of system failures leading to an adverse event)

Requires collection of adequate, accurate, quantitative data to be reliable

Allows for variability and uncertainty (best expresses probabilities as distributions, not single-point estimates)

Identifies variables with the greatest impact on the risk estimates (Sensitivity Analysis)

Quantitative Risk Assessment: Dealing with Variability and

Uncertainty(EC DG SANCO)

Describe all assumptions and constraints.

Represent parameters as probability distributions rather than as single-point-estimate values.

Perform Sensitivity Analysis to demonstrate the influence of assumptions used in the risk assessment on the final risk estimate.

(Answers question: “What if we are wrong about an assumption?”)

Advantages and Weaknesses of Quantitative Risk Assessment

Transparency Assumptions and methods clearly articulated Failure scenarios available for independent

review: elements of risk less likely to be overlooked

Requires collection of adequate, accurate, quantitative data to be reliable For unprecedented hazards no actuarial

information available to estimate probabilities Absent precedents, probabilities for each failure

step are estimated at least partially subjectively Expressing subjective probabilities

numerically implies unjustified level of confidence

Assumes no surprises

PhRMA BSE Risk Model (Bader & al. 1998) and Uncertainty

Bader F et al. Assessment of risk of bovine spongiform encephalopathy in pharmaceutical products. Biopharm 1998;11(1):20-31 and 11(3):18-30

Probability Sources of Uncertainty

Cow infected (herd, age) Quality of surveillance, inspection etc.

Batch contaminated (tissue, slaughter technique)

High-infectivity tissue cross contamination, etc.

Human infectivity per tissue Species barrier estimate

Human infectivity per batch after processing

Limited process validation data, questionable relevance

Human infection per dose Uniformity of susceptibility

Human infections per course Uniformity of susceptibility

Problems with All Risk Assessments

Experts may disagree about assumptions. Elements of risk Probabilities

Models assume no surprises. Bias is unavoidable.

General bias Non-independent probability estimates (Experts may be optimists or pessimists.) Bad-news bias (Probability of a dramatic [recent]

adverse event happening again is overestimated.) Others

Expert bias Contractor bias (“piper’s” bias): seek a desired

outcome Manager bias (shop the experts): seek a desired

outcome Calibration bias (unrealistically narrow confidence

estimates)

Measures to Reduce Risk of Product Contamination.

1. Source materials free of contaminants History of low risk

Materials of animal origin: certificates Materials of human origin: donor questionnaire,

postmortem history Test for contamination

Agent detection (e.g., NAT for HCV, HIV) Surrogate (e.g., antibodies to HBV, HBV, HCV)

Problem No accessible and validated antemortem test

for TSE of bovines or humans Ideal solution

Replace with lower risk material of non-human, non-animal origin:

Often not feasible, especially for established product

Measures to Reduce Risk of Product Contamination.

2. Manufacturing Process: Robust Elimination of Potential Contaminants

Eliminate agents in starting material

Inactivation (preferred) Removal

Prevent cross contamination (“downstream” contamination)

Cleaning Disinfection Discard any residual removed agent safely

Validate Effect (single steps; for “orthogonal” multi-

step should verify additivity) Relevance to actual production

Possible “Rules” for Decisionsin Risk Management

(Morgan MG. Scientific American 1993)

Utility-based decision rules Perform risk-benefit analysis. Maximize net benefit. (Accept a remote risk to achieve a

substantial benefit.) Technology-based decision rules

Use best available technology. (Protect vulnerable populations from

remote risks, even at great cost.)

Regulatory Safeguards against BSE:“Firewalls” and Recent FDA Enhancements

(<http://hhs.gov/news/press/2004pres/20040126.html>)

1. Import prohibitions (1989 USDA)

2. Surveillance of cattle for BSE (1990 USDA)

3. Feed ban: most mammalian proteins prohibited in ruminant feed (1997 FDA)

4. SRM removal from beef 30 mo carcasses, no mechanically recovered meat (2004 USDA)

5. BSE response plans ([1990] 1996 USDA, [1998] 2001 FDA)

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BSE-free sourcing guidances for bovine materials in biologics, drugs, and devices ([1991] 1993 FDA)

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“Downer” and dead cows, SRM30 mo prohibited in FDA-regulated foods (including dietary supplements), cosmetics = USDA regulations [IFR pending]

Enhanced ruminant feed ban [IFR pending] Additional prohibited proteins Mammalian blood Poultry litter Plate waste Dedicated non-ruminant feed: equipment/facilities/production

lines

Possible Additional Safeguards to Consider for Bovine Materials Used in or to Manufacture Injectable Biologic

Products ? “Select” herds of cattle

Fully traceable Certified (how?) never fed (or otherwise exposed

to?) prohibited proteins BSE surveillance—active, adequate (how

evaluated?) ? “Select” individual cattle and tissues

Young ( 30 mo—how old?) (Not feasible for cows fetuses for fetal bovine

serum) SRM removed < 30 mo ( what age?) PrPSc testing? ( what age?; need validated tests)