# Presentation: 547408

## Variant CJD risk associated with human plasma derivatives:  Introduction and overview of risk model for                        US manufactured 
Factor VIII

Steven Anderson, PhD, MPP

Associate Director for Risk Assessment
Office of Biostatistics & Epidemiology
FDA-CBER

TSE Advisory Committee Meeting
October 31, 2005

**Factor VIII**
**Steven Anderson, PhD, MPP**
**Associate Director for Risk Assessment**
**Office of Biostatistics & Epidemiology**
**FDA-CBER**
**TSE Advisory Committee Meeting**
**October 31, 2005**

**Notes:**

Good Morning – My name is Steve Anderson – I am Associate Director for Risk Assessment in the Office of Biostatistics & Epidemiology at The FDA- Center for Biologics Evaluation & Research

I am going to present an update on the FDA risk assessment for vCJD risk potentially associated with US manufactured Factor VIII

As Dr. Scott alluded to in the first talk – the TSEAC provided input on our concept for this model at the February meeting

FDA has been developing a risk assessment model for vCJD risk for US manufacture Factor VIII product –the model is not competed

But during the development phases – several questions arose concerning data inputs that would be used in the model
We have identified several questions and we are seeking input from the committee on the 
scientific Data and approaches that we are proposing to use in the model

## Elements of Risk AssessmentNAS (1983)

**Hazard identification**
***Establishes causality between hazard and  adverse effects***
**Dose response   ****(Hazard characterization)**
***Probability of response – infection or illness ***
**Exposure assessment**
_***Frequency***_*** and ***_***level***_*** of exposure***
***Estimates potential ***_***DOSE***_*** vCJD ID******50***
**Risk characterization**
***Probability of occurrence, severity of adverse effects ***
***Uncertainty ***
***Sensitivity analysis***

**Notes:**
With that I will launch into an overview of the model, discussing some of the model and risk assessment components and also some of the questions that have been raised

As mentioned by Dr. Scott My talk will be followed by several speakers 
I will lay out the basic framework for the model and provide an overview of the components of the model
Each speaker will provide more in-depth information on specific data that we propose to use in the model
We hope after the presentations to have a robust discussion of the science, data and questions raised and get feedback on the suitability of the proposed approaches

So to launch into the model
The committee has seen this slide in a number of my risk assessment presentations
So I will only highlight a few key areas that are relevant to today’s meeting

Risk assessment is a four-step process – the process was described by the National Academies of Science in 1983.

The model that I am going to describe today –would largely fall under the exposure assessment component and models potential exposure to the hazard of interest – which in this case is the vCJD agent.

When evaluating exposure we are largely concerned with 2 aspects  - 
the PROBABILITY of an exposure – or the chance that exposure may occur and
The MAGNITUDE of exposure or AMOUNT of agent that may be present in an exposure.

In estimating potential exposure to vCJD agent 
We estimate the routes by which an individual or population may be exposed to the agent

In this case we are using the model to estimate potential exposure of FVIII recipients to vCJD agent- 
that is the PROBABILITY of exposure and QUANTITY of  vCJD agent  per dose of US manufactured FACTOR VIII products

Just to remind everyone – the exposure assessment will provide us with an estimate of potential Dose vCJD agent recipients may have been exposed to
Exposure assessment – and resulting dose is combined with the dose response relationship to estimate risk
Risk is detailed in the Risk Characterization component of this assessment – which of course has not been done yet.

I’ll again emphasize the relationship between exposure assessment or Dose – and dose-response – and how that is used to estimate RISK

## Risk AssessmentNAS (1983)

**Risk Assessment is conducted when information is limited and **_**uncertainty high**_
**Value of Risk Assessment**
**Provides estimate of risk**
**Details the Uncertainties **
**Determine effectiveness of Mitigations**
**Identifies data gaps and research priorities**

**Notes:**
As a reminder of why Risk assessments are conducted
Risk Assessments are conducted when information is limited – making uncertainty about a potential hazard high

I have listed several valuable aspects of risk assessment

Risk Assessment
Provides estimate of risk
Details the Uncertainties 
Determine effectiveness of Mitigations
Identifies data gaps and research priorities

## Risk Assessment

**Uncertainty**
**Arises in risk assessment when:**
**Only limited information is available**
**Data are lacking**
**Use of assumptions / expert opinion**
**Errors in measurement or data collection**
**Incorrect specification of model**

**Notes:**

Uncertainty is a pervasive – underlying component of risk assessment

Uncertainty Arises in risk assessment (for a number of reasons that I have outlined ) when:

Only limited information is available
Data are lacking

The first two  items lead risk assessors to use assumptions and expert opinion to fill in information gaps to develop parameters
Use of assumptions / expert opinion

Of course there can be 
Errors in measurement or data collection
That can be an issue in the TSE field – if there are problems / limitations with data that are generated experimentally – such as contamination problems, etc.

And finally there can be - 
Incorrect specification of model
Meaning the model may not accurately reflect all of necessary elements that contribute to risk – such a model might underestimate the risk 
As an example – some of the predictive epidemiological models – only model potential vCJD illness in individuals who are homozygous for Methionine at codon 129 PrP gene –representing approximately 40% of the UK population– and don-t account for potential infection and vCJD cases in other genotypes such as  heterozygous MM  Methionine Valine at position 129Prp or homozygous Valine at that position

## FDA Risk Assessment: vCJD risks for US manufactured Factor VIII

**Factor VIII assessment under development**
**Models vCJD risk for Factor VIII made in 2002**
**Assessments for additional years possible - 1999**
**Beginning of process to assess risks for plasma derivatives – in future may:**
**Assess vCJD risks – additional product classes**
**Possibly assess risk by specific product, per individual, etc.**
**Process model – analyzes**** **
**Probability & quantity vCJD agent in plasma pools**
**Reduction in levels vCJD ID****50**** in manufacturing**
**Quantity Factor VIII used – exposure vCJD ID****50**

**Notes:**
Again as I indicated the FVIII assessment is under development

We chose to model vCJD risk for Factor VIII manufactured the year 2002
Because it is a recent year, we have significant data for that year, and it is the first year the vCJD geographic deferrals for blood and plasma donors were fully in place

It will be possible to model prior and future years – we are proposing to model risk for 1999 – to estimate risk prior to implementation of vCJD donor deferrals

I do want to emphasize that risk assessment for plasma derivatives is a relatively new endeavor at FDA-CBER
And our efforts are just the beginning of a process – and possibly a long process for estimating potential vCJD risks for plasma derivatives.

We are starting with US manufactured Factor VIII –eventually we may develop risk assessments for other plasma derivative product classes such as Factor IX and others

Possibly we can further extend our efforts to address risk by specific products, per individual, and other groups

Our model is a process model – that evaluates risk that may be associated with starting materials used in manufacturing, manufacturing processes, and utilization

As with the Facto XI model presented at the February TSEAC meeting we have developed 
A Process model –that  analyzes such factors and processes such as:
Probability & quantity vCJD agent in plasma pools
Reduction in levels vCJD ID50 in manufacturing
Quantity Factor VIII used by recipients – thereby enabling us to estimate an individual or population’s exposure to  vCJD ID50

## Overview of vCJD and US manufactured Factor VIII Risk Assessment Model

**Notes:**
I will provide a brief overview of the proposed model that we are developing - in the form of a diagram- for vCJD risk for US manufactured Factor VIII 

That lays out the various components in the model, the input data and the outputs we expect to generate from the model

## Slide 7

**Notes:**
We have divided the model into 4 components at this time
To orient you to the diagram inputs are generally on the left and represent the data and parameters used in the model while on the left are the outputs or results from each component of the model – which in turn feed into the next component of the model

The output estimated in Module 1 of the model  - is vCJD prevalence in the United Kingdom
As I will mention in a moment this estimated UK vCJD prevalence is the foundation of the model – so it is important to have a robust an estimate as possible.  
FDA is proposing to use results from two different types of approaches for estimating UK vCJD prevalence

Module 2 estimates the prevalence of US plasma donors –
Model assumes that some plasma donors with travel history to UK, France or Europe since 1980 may have been exposed to BSE agent
The model further adjusts for donor travel – by duration of travel, specific year of travel and donor age
Although donors with this specific travel history may be at risk for vCJD infection – most donors are removed from the donor pool by the deferral policies for blood donors – we assume the rate of removal is 90% or greater.
OUTPUTS predicted by this component are estimates of the potential number of vCJD infected donors and donations with vCJD that enter plasma pools.

MODULE 3 considers factors important in Factor VIII processing and Manufacture including plasma pool size, quantity vCJD agent in pool, and the reduction of levels of vCJD agent by manufacturing processes.
In addition to the number of potential vCJD donors that may donate to plasma pools,  Reduction is perhaps the second most critical element in the model in reducing risk.  
OUTPUTS from Module 3 include estimates of the percentage of plasma pools and vials potentially containing vCJD agent – and then also an estimate of the potential quantity of vCJD agent that may be present in a FVIII vial manufactured from a pool containing a donation from a vCJD infected donor.

MODULE 4 – estimates the utilization of FVIII by recipients – to estimate annual exposure of FVIII recipients to the vCJD agent

## Module 1 Prevalence of vCJD in United Kingdom

**Proposed Modeling Approaches**
- Two major sources of UK vCJD prevalence data
- A.  Predictive Modeling based on vCJD cases in UK
- B.  Surveillance data – examination tonsil/appendix samples
- Disparity of approximately _10 to 100 fold_ between the two approaches

**Notes:**

FDA is proposing to use two different approaches to estimate prevalence of vCJD in the US
those approaches include 
Predictive mathematical modeling and 
(B) Surveillance data- based on examination tonsil/appendix samples. 

There is a disparity in the predictions and information offered by these two approaches in the current literature of approximately 10 to 100 fold .  With the Surveillance data generating a higher estimate at this point in time.

##  Module 1Prevalence of vCJD in United Kingdom

**A. Predictive mathematical models**** **
**	****Some of data we may use (select sample – many others!):**
**	****(1) Ghani et al 2003**** **
**vCJD estimate median 100 cases (10 – 2,600  - 95% CI)**
**Median  1 in 500,000**
**(2)  Boelle, et al 2003**
**vCJD estimated cases range 183 to 304 cases**
**(3) Llewyn *****et al***** 2004**
**vCJD infection     1 in 15,000   to   1 in 30,000**
**Approximately 1,000  - 2,000 infections **
**Include all genotypes in estimate  - codon 129 PrP – MM, MV, VV**

**Notes:**

To estimate the vCJD prevalence in the UK population.
A number of mathematical models estimating the number of vCJD cases in the UK are in the literature – 
in general they rely on the annual numbers of cases of diagnosed vCJD in the UK- as a basis for predicting the number of future cases of vCJD.  
In the past three years the number of cases predicted by these models have begun to decrease and this is reflected in the more recent model estimates.

IT IS IMPORTANT TO EMPHASIZE THAT THE RESULTS FROM THESE MODELS REPRESENT A SNAPSHOT IN TIME – AND THE RESEARCH IN THIS AREA IS EVOLVING TO CONSIDER NEW INFORMATION  - SUCH AS GENETIC SUSCEPTIBILITY, ETC.

Dr. Ghani will present more in-depth information on UK vCJD prevalence – some of the recent modeling efforts –

I’ve listed the results from one of her many research efforts – this paper in 2003 estimates 100 clinical cases of the disease that could occur in the future with a 95% CI of 10 to 2,600 cases.  That works out to a median of 1 case in 500,000 people.

The second paper I have listed is largely by a French research group - Boelle, et al 2003  suggested that the vCJD estimated cases would range 183 to 304 cases

A recent estimate by Llewyn in 2004 estimates the number of people infected with vCJD ranges from 1/15,000 to 1 / 30,000
vCJD infection     1 in 15,000   to   1 in 30,000
Approximately 1,000  - 2,000 infections 
Include all genotypes in estimate  - codon 129 PrP – MM, MV, VV

Again, the results here are different even among the modeling approaches – for instance,  Llewyn et al 2004
Potentially estimates a higher prevalence incorporating new information that additional genotypes at codon129 PRP may be susceptible to vCJD infection
If or how the infections in these individuals may manifest themselves is unknown – the infections may not lead to illness or symptomatic cases? But remains to determine whether these infections may pose a risk to the blood and plasma supplies

## Module 1 Prevalence of vCJD in United Kingdom

**B.  Surveillance data – tissue samples UK patients**
**Tonsil/appendix surveillance study ****(Hilton, et al. 2004)**
- 3 prion positive samples in 12,674 samples tested
- Mean of **1 positive in 4,225** individuals
- Mostly in 20 – 30 yr old patients
- Approximately 13,000 vCJD infected UK individuals
- Data would be further age adjusted – using reported UK vCJD cases age profile

**Notes:**
The second type of approach for estimating prevalence of vCJD in the UK
is
B.  Surveillance data – tissue samples UK patients

Based on information
Tonsil/appendix surveillance study (Hilton, et al. 2004) – Dr. Ghani was also an author on this paper
 in which
3 prion positive samples in appendix tissue in 12,674 samples tested
Mean of 1 positive in 4,225 individuals
Mostly in 20 – 30 yr old patients
A rough estimate would suggest that approximately 13,000 vCJD infected individuals in the UK – but if the calculations were age adjusted the estimate would be fewer predicted cases

As the committee may remember when we presented the FXI model in February
 THESE DATA WERE USED IN THE FXI MODEL AS THE UK PREVALENCE – along with the 95% confidence intervals on either side of the mean

We thought at that time that they may capture prevalence among other populations with different genetic susceptibilities and asymptomatic cases that would never progress to clinical illnes

At the previous TSEAC meeting the committee recommended adjusting prevalence data for age specificity 
Our plan is the
Data would be further age adjusted – using reported UK vCJD cases age profile

## Module 1 Prevalence of vCJD in United Kingdom

_**Uncertainties**_** of Proposed Modeling Approaches**
**Predictive Modeling** based on vCJD cases in UK
- Only estimate clinical cases of MM codon 129 individuals
- Use of assumptions – incubation period, time of infection, etc
**Surveillance data** – examination tonsil/appendix samples
- vCJD agent in appendix – may not have agent in blood
- May not become symptomatic
- Overestimate  (Sample size relatively small for rare disease)
- Underestimate vCJD prevalence  - in one infected case vCJD agent not in appendix
**Generally neither approach adequately address:**
- Clinical or asymptomatic cases MV codon 129, or VV 129 PrP
- vCJD infections that don’t progress to symptomatic disease

**Notes:**
Prevalence of vCJD in United Kingdom

All data – and approaches have limitations and uncertainties associated with them

Uncertainties of Proposed Modeling Approaches

Predictive Modeling based on vCJD cases in UK
Only estimate clinical cases of MM codon 129 individuals
Use of assumptions – incubation period, time of infection, etc

Surveillance data – examination tonsil/appendix samples
MAJOR ISSUE HERE IS THAT IT IS IMPOSSIBLE TO KNOW THE CLINICAL OUTCOMES OF THE PATIENTS FROM WHICH THERE WERE POSITIVE SAMPLES
vCJD agent in appendix – may not have agent in blood
May not become symptomatic
Overestimate  (Sample size relatively small for rare disease) 
Underestimate vCJD prevalence  - in one infected case vCJD agent not in appendix

Generally neither approach adequately address:
Clinical or asymptomatic cases MV codon 129, or VV 129 PrP
vCJD infections that don’t  and may never progress to symptomatic disease

## Module 1Prevalence of vCJD in United Kingdom

**Estimation of prevalence vCJD in UK population**
_**Critical**_** **parameter in model – used to estimate vCJD prevalence for:
- France
- Europe
**Plasma donors in United States**

**Notes:**
Estimation of prevalence vCJD in UK population

Critical parameter in model – used to estimate vCJD prevalence for: 

France
Europe
THIS IS DONE IN A RELATIVE WAY – USING THE CONCEPT OF RELATIVE RISK

FINALLY UK vCJD prevalence is used to predict prevalence for
Plasma donors in United States

Based on relative risk – that is, vCJD risk relative to the UK risk or prevalence

## Module 2Prevalence vCJD in US plasma donors

**Proposed Modeling Approach**
- Estimate size of US plasma donor population travel history to UK, France or Europe since 1980
- Determine travel characteristics from survey data
- Adjust travel data by several factors (duration of stay, year, etc.)
- Estimate probability of infection in individual donors
- Add up potential number cases for US plasma donor groups
- Apply effectiveness of donor deferral policy
**Model output – predict number of:**
- Potential vCJD infected US plasma donors
- vCJD infected donors deferred from donation
- Potential donations with vCJD agent

**Notes:**
Continuing on Module 2
Estimation of Potential Prevalence vCJD in US plasma donors

Our Proposed Modeling Approach includes

Estimate size of US plasma donor population with a travel history to UK, France or Europe since 1980
Determine travel characteristics from survey data (country of travel, year,  duration, age of donor, etc)	
Adjust travel data by several factors such as (duration of stay, year, etc.)
Estimate probability of infection in individual donors
Add up potential number cases for US plasma donor groups
Apply effectiveness of donor deferral policy

Model output – predict number of:
Potential vCJD infected US plasma donors
vCJD infected donors deferred from donation
Potential donations with vCJD agent

The probability and quantity of vCJD ID50s in a US plasma pool is directly related to the prevalence of vCJD in the US donor population – we assume that the vCJD prevalence in the US donor population would be very low.

## Module 2Prevalence vCJD in US plasma donors

**vCJD in US donors possible from **_**dietary exposure**_** to BSE agent during travel**
_**Current policy – Defers donors with travel history**_**:**
- UK         _>_ 3 months   - 1980 – 1996
- France   _>_ 5 years      - 1980 – present
- Europe   _>_ 5 years  - 1980 - present (blood donation only)
- Estimated 90% - 99% effective eliminating vCJD donors / risk
_**Residual risk**_** -  Two** donor groups of interest
** ****1) ****Deferrable risk **
**    ****1% - 10% with deferrable travel history risk but donate**
-  2) **Short duration travel**
- 	  UK         < 3 months - 1980 – 1996
-    	  France   < 5 years    - 1980 – present
- 	  Europe   < 5 years  - 1980 - present (blood donation only)

**Notes:**
Continuing on Module 2
Estimation of Potential Prevalence vCJD in US plasma donors

In our previous slide we propose to estimate the number of potential vCJD infected plasma donors in the United States

Up front I wanted to say that most of those donors will not donate because they will be deferred because of the current geographic deferral policy for vCJD that is in place.

Now going back to the potential for donors potentially with vCJD in the US

Our assumption in the model is that
vCJD in US donors possible from dietary exposure to BSE agent during travel 
Specifically travel to the UK, France or Europe since 1980.

The Current deferral policy addresses travel to these regions specifically the policy is as shown on the slide

Current policy – Defers donors with travel history:
UK         > 3 months   - 1980 – 1996
France   > 5 years      - 1980 – present
Europe   > 5 years  - 1980 - present (blood donation only)
There is no deferral for Source Plasma Donors that traveled to Europe since 1980

We have estimated that the policy is
90% - 99% effective eliminating vCJD donors / risk

Residual risk  (remaining after implementation of the deferral policy)-  with the policy in placer there are still potential sources of vCJD infection and risk
 Two possible donor groups of interest
That includes those with
 1) Deferrable risk  
But were not deferred for whatever reason that may include - 
    1% - 10% with deferrable travel history risk but ( still continue to ) donate

FOR RESIDUAL RISK   - THE SECOND POPULATION OF INTEREST  THAT MAY BE AT RISK FOR vCJD INFECTION
IS THOSE DONORS WITH A HISTORY OF TRAVEL SPECIFICALLY   
  2) Short duration travel
	  UK         < 3 months - 1980 – 1996
   	  France   < 5 years    - 1980 – present
	  Europe   < 5 years  - 1980 - present (blood donation only)

We propose to model the potential vCJD risk arising from these two populations

## Module 2Prevalence vCJD in US plasma donors

**Concept of Relative Risk**
- Used to estimate vCJD prevalence France and Europe relative to UK prevalence
- Based on BSE exposure, number vCJD cases, etc.

|  | Relative 
Risk | Estimated mean relative 
vCJD Prevalence |
| --- | --- | --- |
| UK | 1 |                                UK vCJD prevalence |
| France | 0.05 |         0.05      x       UK vCJD prevalence |
| Europe | 0.015 |         0.015    x       UK vCJD prevalence |
| Military | 0.035 |         0.035    x       UK vCJD prevalence |
| Euroblood |       0.015 |         0.015    x       UK vCJD prevalence 
                              ( x age adjustment Euro donor) |

**Notes:**
Continuing on Module 2
Estimation of Potential Prevalence vCJD in US plasma donors

Concept of Relative Risk
Used to estimate vCJD prevalence France and Europe relative to UK prevalence 
Based on BSE exposure, number vCJD cases, etc.

Relative risk estimate will become a multiplier against UK vCJD prevalence in the model 

	Relative 
Risk	Estimated mean relative 
vCJD Prevalence
UK	1	                               UK vCJD prevalence
France	0.05	        0.05      x       UK vCJD prevalence
Europe	0.015	        0.015    x       UK vCJD prevalence
Military	0.035	        0.035    x       UK vCJD prevalence
Euroblood	      0.015	        0.015    x       UK vCJD prevalence 
                              ( x age adjustment Euro donor)

Euroblood was blood that was collected in three regions of Europe and transfused into US recipients
Mostly in the New York City region of the United States

## Module 2 Potential vCJD Prevalence in US Plasma Donors

**Relative risk for US plasma donor with travel history to UK, France or Europe since 1980**
**FDA model adjusted relative risk for vCJD                    over 23 year period (1980 – 2002) based on:**
- Duration of Travel
- Relative risk is adjusted on a per month or per day basis
- Specific year(s) of travel
- Accounts for variation in BSE epidemic / exposure
- Age of donor
- To apply age specific rates for vCJD in UK (median age 28yrs)

**Notes:**
Continuing on Module 2
Estimation of Potential Prevalence vCJD in US plasma donors

Relative risk for US plasma donor with travel history to UK, France or Europe since 1980

FDA model proposes to adjust relative risk for vCJD over 23 year period (1980 – 2002) based on:

Duration of Travel – this is perhaps the largest adjustment to risk 
Relative risk would be adjusted on a per month or per day basis

Specific year(s) of travel 
Accounts for variation in BSE epidemic / exposure – we would link this specifically to the BSE epidemic curve to specifically account for potential donor exposure to BSE agent in a specific year or years

Age of donor
To apply age specific rates for vCJD in UK (median age 28yrs)  
Much less vCJD age-specific risk for older individuals for instance those > 60 yrs of age

## Module 2 Potential vCJD Prevalence in US Plasma Donors

**Propose to model two types of                    plasma donors **
**1.**  **Source Plasma donors** (> 80% donations)
- Age specific donation rates
**2.  Recovered Plasma donors** (< 20% donations)
- Age specific donation rates

**Notes:**
Continuing on Module 2
Estimation of Potential Prevalence vCJD in US plasma donors

Propose to model two types of                    plasma donors 

Source Plasma donors which make up greater than (> 80% donations)
     We would use information on 
Age specific donation rates – and incorporate those into the model – since we are doing age specific adjustments for many components of the model

Recovered Plasma donors which make up less than (< 20% donations)
    again we would also apply 
Age specific donation rates  - to the recovered donor plasma population

## Module 2Estimation Potential vCJD Prevalence in US Plasma Donors

**Plasma Donor travel estimated from            survey data**
**Survey – random sample of blood donors by American Red Cross**
- Conducted Dec 1998 & Jan 1999
- Queried travel history and accumulated stay information for UK, Europe and/or (France) during period 1980 - 1996

**Notes:**
Continuing on Module 2
Estimation of Potential Prevalence vCJD in US plasma donors

Plasma Donor travel estimated from            survey data

Survey – random sample of blood donors by American Red Cross     

Conducted Dec 1998 & Jan 1999

Queried travel history and accumulated stay information for UK, Europe and/or (France) during period 1980 – 1996

We do have to make some assumptions and infer travel to France from this data

## Module 2Estimation Potential vCJD Prevalence in US Plasma Donors

**Modeling effectiveness of geographic deferral policy for travel to UK, France and Europe **
**Data be discussed by Dr. Alan Williams**
**Potential values that could be used in FDA model for effectiveness vCJD deferral policies**
- Reduces 90% to 95% of vCJD risk from first-time donations
- May reduce 99% vCJD risk from repeat donors

**Notes:**
Continuing on Module 2
Estimation of Potential Prevalence vCJD in US plasma donors

Modeling effectiveness of geographic deferral policy for travel to UK, France and Europe 

Data be discussed by Dr. Alan Williams

Potential values that could be used in FDA model for effectiveness vCJD deferral policies

Reduces 90% to 95% of vCJD risk from first-time donations
May reduce 99% vCJD risk from repeat donors

We estimate that for plasma donors greater than 90% of donors are repeat donors

## Module 2Estimation Potential vCJD Prevalence in US Plasma Donors

**When is vCJD agent present in blood during incubation period?**
**Detailed discussion of data by Dr. David Asher**
**Two potential approaches could be modeled**
- During entire incubation period
- Assumption used in FDA Factor XI risk assessment
- During last half of incubation period?
- Brown, et al. 1999 prions in blood later in incubation period
- Modeling would be complex
- Increased uncertainty
- Assumptions would be made about duration incubation periods

**Notes:**
Continuing on Module 2
Estimation of Potential Prevalence vCJD in US plasma donors

When is vCJD agent present in blood during incubation period?

Detailed discussion of data by Dr. David Asher

Two potential approaches could be modeled

The vCJD agent is present in blood 
During the entire incubation period
Assumption used in FDA Factor XI risk assessment

During last half of incubation period?
	Animal experiments done by
Brown, et al. 1999 prions in blood later in incubation period
Modeling would be complex
Increased uncertainty
Assumptions would be made about duration incubation periods

## Module 2Estimation Potential vCJD Prevalence in US Plasma Donors

**Uncertainties**
**Survey conducted on whole blood (recovered plasma donors)**
**No survey on travel characteristics Source Plasma donors**
**Source plasma donors may travel less**
**Blood donor travel information may overestimate risk for Source Plasma**
**Estimation deferral effectiveness a challenge – because self-deferral**
**Estimation of vCJD agent’s presence in blood – from animal data may not be accurate for humans**

**Notes:**
Continuing on Module 2
Estimation of Potential Prevalence vCJD in US plasma donors

Uncertainties

AGAIN EVERY TYPE OF DATA HAS SOME LIMITATION AND UNCERTAINTY ASSOCIATED WITH IT

Survey conducted on whole blood (recovered plasma donors)

No survey on travel characteristics Source Plasma donors
	Anecdotally it is believed that 
Source plasma donors may travel less  - in which case the 
Blood donor travel information may overestimate risk for Source Plasma

Estimation of  deferral effectiveness is  a challenge – mostly because many donors likely self-defer
So it is difficult to know the total number of donors that have been impacted by the policy since many of them likely never present for donation

Estimation of vCJD agent’s presence in blood – from animal data ( may or) may not be accurate for humans
We have little information on if it is only present later in the infection or not, and that info is from animal data

## Module 3Factor VIII Processing

**Proposed Modeling Approach**
- Estimation _probability_ plasma pool contains vCJD donation
- Estimation _quantity_ vCJD ID50 per ml plasma and per pool
- Efficiency of exposure through   i.v.  versus i.c. route
- Log10 reduction in quantity iv ID50
**Model output to predict :**
- Percentage plasma pools with vCJD agent
- Percentage vials with vCJD agent
- Quantity vCJD agent per vial

**Notes:**
Moving on to Module 3
Factor VIII manufacturing and Processing

Our 
Proposed Modeling Approach
Is to estimate the following elements from data inputs or from model outputs including: 
Estimation probability plasma pool contains vCJD donation
Estimation quantity vCJD ID50 per ml plasma and per pool
Efficiency of exposure through   i.v.  versus i.c. route 
Log10 reduction in quantity iv ID50

We would then use the
Model output to predict :
Percentage plasma pools/vials with vCJD agent
Quantity of vCJD agent per vial or per unit of Factor VIII

## Module 3Factor VIII Processing

**Proposed modeling approaches for estimation quantity vCJD ID****50**** per ml plasma and in pool**
**Data to be discussed by Dr. David Asher**
- Data:  ic ID50 per ml blood
- 	Propose to use triangular distribution with
- Minimum         	    0.1
- Most likely      	  10
- Maximum       	310

**Notes:**
Moving on to Module 3
Factor VIII manufacturing and Processing

Proposed modeling approaches for estimation quantity vCJD ID50 per ml plasma and in pool

Data to be discussed by Dr. David Asher

Data:  ic ID50 per ml blood
	Propose to use triangular distribution with
Minimum         	    0.1
Most likely      	  10
Maximum       	310 

The maximum value for infectivity in the blood that we identified in the literature was 310 ID50 per ml of blood,

At this time – these represent ranges in the relevant data – we are providing these values as a guideline but realize the committee may choose other values for the range depending on your understanding of the data

## Module 3Factor VIII Processing

**Proposed approaches estimation efficiency of exposure route to vCJD ID****50**
- FDA Factor XI risk assessment - assumption with range _5 to 10 fold_ (Kimberlin, et al  1996)
- Recent unpublished data suggest adjustment _**1 to 5 fold**_ for efficiency of intracerebral vs. intravenous route exposure
**FDA proposes to use estimate of **_**1 to 5 fold**_** for adjustment of efficiency of intracerebral vs. intravenous route exposure**

**Notes:**
Moving on to Module 3
Factor VIII manufacturing and Processing

Proposed approaches estimation efficiency of exposure route to vCJD ID50

FDA Factor XI risk assessment - assumption with range 5 to 10 fold (Kimberlin, et al  1996) and data from Dr. Paul Brown’s laboratory

Recent unpublished data suggest adjustment 1 to 5 fold for efficiency of intracerebral vs. intravenous route exposure

FDA proposes to use estimate of 1 to 5 fold for adjustment of efficiency of intracerebral vs. intravenous route exposure –erring on the side of caution that the iv route might be more efficient at transmitting infection than we had previously thought

## Module 3Factor VIII Processing

**Proposed approach estimation of **
**Plasma pool size in FDA model**
**Number of donations per plasma pool used in manufacturing ranges from 20,000 donations up to 60,000 donations**
**FDA needs more accurate information on size of pools used in manufacturing**
**FDA proposes to use a bimodal distribution – indicating plasma pools  most likely contain 20,000 donations or 60,000 donations**

**Notes:**
Moving on to Module 3
Factor VIII manufacturing and Processing

Proposed approach estimation of 
Plasma pool size in FDA model

Based on very limited information that we have
The Number of donations per plasma pool used in manufacturing of Factor VIII ranges from 20,000 donations up to 60,000 donations

FDA needs more accurate information on size of pools used in manufacturing

Absent any additional information on this variable 
Based on the available information we have     
FDA proposes to use a bimodal distribution – indicating plasma pools  most likely contain 20,000 donations or 60,000 donations

## Module 3FVIII Processing

**Proposed modeling of reduction vCJD ID****50**** during FVIII processing**
**Detailed information to be presented by Dr. Dorothy Scott**
- Some reduction levels vCJD ID50 expected to occur during processing and manufacture of Factor VIII
- Designations for degree FVIII purity (intermediate or high purity) may have little relationship to level of vCJD ID50 clearance
**FDA proposes 3 values for range Log****10**** reduction ID****50**** during processing**
-     2 Log10 ,  5 Log10 ,  8 Log10,
- Distributions about these values – will capture uncertainty
- Possible distributions  1-3 Log10, ,  4 – 6 Log10, , 7 – 9 Log10, , etc.

**Notes:**
Moving on to Module 3
Factor VIII manufacturing and Processing

Proposed modeling of reduction vCJD ID50 during FVIII processing

Detailed information to be presented by Dr. Dorothy Scott

Some reduction levels vCJD ID50 expected to occur during processing and manufacture of Factor VIII

Important to emphasize that 
Designations for degree FVIII purity (intermediate or high purity) may have little relationship to level of vCJD ID50 clearance

FDA proposes 3 values for range Log10 reduction ID50 during processing

    2 Log10 ,  5 Log10 ,  8 Log10,

We propose to generate three different model outputs around each of these values

We propose to use distributions about these values

Distributions about these values – will capture uncertainty and variability in the estimates
Possible distributions  1-3 Log10, ,  4 – 6 Log10, , 7 – 9 Log10, , etc.

## Module 3FVIII Processing

**Uncertainties in the data**
**Only limited amount of data available of TSE reduction for a small number processing steps and few products**
**Levels of reduction achieved with spiked infectivity may not accurately reflect levels achieved during manufacturing**
**Experimental data obtained for other TSE agents and not specifically for vCJD agent **
**Does addition of orthogonal reduction steps reflect actual reduction ID****50**** during manufacturing?**** **

**Notes:**
Moving on to Module 3
Factor VIII manufacturing and Processing

Uncertainties in the data

Only limited amount of data available of TSE reduction for a small number processing steps and few products

Levels of reduction achieved with spiked infectivity may not accurately reflect levels achieved on endogenous infective material used in  manufacturing

Experimental data obtained for other TSE agents and not specifically for vCJD agent – may add to uncertainty

Does addition of orthogonal reduction steps reflect actual reduction ID50 during manufacturing?
Not entirely known whether reduction steps should be added or not

The committee can probably think of many other sources of uncertainty as well in these data for FVIII manufacturing and processing

## Module 4 Utilization of Factor VIII

**Proposed Modeling Approach**
**Inputs:**
- Percentage vials with vCJD agent
- Quantity vCJD agent per vial
**Annual utilization / dose Factor VIII per patient**
**Model output to predict :**
- Annual **potential dose vCJD ID****50** per patient
- Prediction of risk of vCJD infection based on
-     animal dose-response information

**Notes:**
Moving on to Module 4
Utilization of Factor VIII

By the time we get to this component of the model we are beginning to combine the results of many components of the model together – 
UK vCJD prevalence is used to help us estimate
vCJD prevalence in US plasma donors – which in turn tells us the number of potential vCJD infected donors and donations – greater than 90% of which are deferred
We link this information to the number of donations potentially with vCJD agent that might find their way into plasma pools
This finally gets us to module 4 where we

Proposed Modeling Approach

To estimate:
Percentage vials with vCJD agent
Quantity vCJD agent per vial
Annual utilization / dose Factor VIII per patient

Model output to predict :
Annual dose vCJD per patient
Prediction of risk of vCJD infection based on 
    animal dose-response information

## Module 4 Utilization of FVIII

**Utilization to be discussed by Dr. Mark Weinstein**
** **
**Utilization Factors being considered for model**
- Severity of Hemophilia A
- Severe, Moderate and Mild
- Treatment regimens
- Prophylaxis and sporadic
** ****Utilization data from CDC Hemophilia Treatment Centers may be used in model**
- 3000 patients followed   1993 – 1998 utilization based on review of medical chart
- If available – may use additional data sources from medical databases

**Notes:**
Moving on to the topic of 

Utilization of Factor VIII

Utilization to be discussed in detail by Dr. Mark Weinstein

Utilization Factors being considered for model
Severity of Hemophilia A
Severe, Moderate and Mild

Treatment regimens
Prophylaxis and sporadic  - per bleeding episode

 Utilization data from CDC Hemophilia Treatment Centers may be used in model

3000 patients followed   1993 – 1998 utilization based on review of medical chart

If available – may use additional data sources from medical databases  

Including data from CMS – or Center for Medicare – Medicaid Services , HMOs or other care providers

## Module 4 Utilization of FVIII

**Uncertainties**
**Utilization data – not most current and may not accurately reflect current prescribing practices**
**Patients on multiple products – utilization not separately reported for each **
**Patients may move among categories (prophylaxis to episodic, etc.) difficult accurately capture in estimate**
**To reduce uncertainty – FDA is seeking additional sources of FVIII utilization data**** **

**Notes:**
Moving on 
 Module 4
Utilization of Factor VIII

Uncertainties

Utilization data – not most current and may not accurately reflect current prescribing practices –

 CDC Hemophilia treatment center data was collected from 1993 – 1998 so we would have to extrapolate and estimate utilization for 2002

Patients on multiple products – utilization not separately reported for each 

Patients may move among categories (prophylaxis to episodic, etc.) difficult accurately capture in estimate

To reduce uncertainty – FDA is seeking additional sources of FVIII utilization data

The type of data that would be very useful is information on number of units used, products used, severity of disease, treatment regimens, and demographic information 

## Exposure Assessment

**Should the FDA model address apparent cumulative nonlinear effects of                        repeated dosing?**** **
**Data to be discussed by Dr. Mark Weinstein**
- Single Dose
- Repeated / Cumulative Doses  (Diringer H, et al. 1998, Jacquemot, et al. 2005)
- Modeling the risk of repeated / cumulative doses would be a challenge and increase uncertainty in risk estimate
- Limited data suggest that in some cases there may be an added nonlinear increase in infection rates with repeated dosing
**FDA proposes  to model cumulative vCJD exposure **_**per year**_** assuming a linear ID****50**** dose-response**

**Notes:**
Moving on to Module 4
Utilization of Factor VIII

Should the FDA model address apparent cumulative nonlinear effects of                        repeated dosing? 

Data to be discussed by Dr. Mark Weinstein

Single Dose
Repeated / Cumulative Doses  (Diringer H, et al. 1998, Jacquemot, et al. 2005)

Modeling the risk of repeated / cumulative doses would be a challenge and increase uncertainty in risk estimate
Limited data suggest that in some cases there may be an added nonlinear increase in infection rates with repeated dosing

FDA proposes  to model cumulative vCJD exposure per year assuming a linear ID50 dose-response

## Exposure Assessment

**Exposure assessment of FDA model will provide estimate of **
**potential vCJD ID****50**** dose**
**Estimated dose**** from model– coupled with                                              dose-response relationship for vCJD agent**
**Model will assume: vCJD ID****50**** is a linear dose-response**
** **
**            ****Estimated RISK**** ****= Probability vCJD infection**
** **

|   Dose | Probability of infection |
| --- | --- |
|  1  ID50 | 50 % |
| 0.1 ID50 | 5 % |
|     etc. |  etc. |

**Notes:**
Moving on to

Exposure assessment of FDA model will provide estimate of 
potential vCJD ID50 dose

Estimated dose from model– coupled with dose-response relationship for vCJD agent

Model will assume: vCJD ID50 is a linear dose-response
Again this linear dose response has significant uncertainties – for instance – what is the meaning if an individual is exposed to a fraction of a dose of an ID50

So in this table does 0.1 ID50 really equate to a 5% probability of an infection  
There are two ways to think about this

(1)
Assuming the dose response is linear and fractional ID50s can give rise to infection
If  20 individuals are exposed to 0.1 ID50 then it is likely that 1 of the individuals would become infected.

(2) 
Alternatively, it may be that  one ID50 is an indivisible unit needed to initiate infection.

Using the same example above , If  20 individuals are exposed to a dose of 0.1 ID50 then it is likely that 1 of the individuals would be exposed to 1 ID50  and infected.

            Estimated RISK = Probability vCJD infection

## Exposure Assessment

**Exposure to **_**Fractional ID**__**50**_** or  **_**Indivisible ID**__**50**_** **
**(1) Fractional ID****50**** infection**
**20 individuals exposed to 0.1 ID****50**** then**
**likely that 1 individual exposed to ****0.1 ID****50**** would become infected**
**(2) Indivisible ID****50**** infection**
**20 individuals exposed to 0.1 ID****50**** then**
**Probability of 0.1 or 10% of receiving **_**one ID50**_
**Implies that 19 individuals receive no ID****50****  and 1 receives **_**1 ID**__**50**_** **
**likely that 1 individual exposed to ****1 ID****50****  and infected **
** **

**Notes:**
Exposure to Fractional ID50 or  Indivisible ID50 

(1) Fractional ID50 infection
20 individuals exposed to 0.1 ID50 then
likely that 1 individual exposed to 0.1 ID50 would become infected

(2) Indivisible ID50 infection

20 individuals exposed to 0.1 ID50 then
Probability of 0.1 or 10% of receiving an ID50
Implies that 19 individuals receive no ID50  and 1 receives 1 ID50 

likely that 1 individual exposed to 1 ID50  and infected 

Again Most people seem to favor the first way of thinking about TSE infectivity and the ID50 dose response

## Dose response (vCJD)

**Uncertainties**
**Factor VIII risk assessment uses **_**Animal ID**__**50**__** as linear dose-response**_** to estimate human risk !**
**Animal data limited – adding uncertainty to dose-response**
**Human data not available**
**Development of a **_**human dose response**_** model is not possible at this time**

**Notes:**

A bit on     Dose response (vCJD)

Uncertainties

Factor VIII risk assessment uses Animal ID50 as linear dose-response to estimate human risk !

Animal data limited – adding uncertainty to dose-response

Human data not available

Development of a human dose response model is not possible at this time

## Risk CharacterizationvCJD risk for Factor VIII

**Conclusions:**
**Estimated risk of infection based on level of exposure (dose) can be predicted using model**
**Risk Prediction based on animal data and animal dose response**
**Therefore risk estimates will be **_**highly uncertain**_** **
**Risk assessment will highlight data gaps and uncertainties**
**Risk estimates do provide information on relative magnitude of risk for risk management purposes**
**    **

**Notes:**

Some concluding thoughts on 
vCJD risk for Factor VIII

Conclusions:

Estimated risk of infection based on level of exposure (dose) can be predicted using model

Risk Prediction based on animal data and animal dose response

Therefore risk estimates will be highly uncertain 

Risk assessment will highlight data gaps and uncertainties

This information will likely improve as research makes headway on TSEs
Subsequent iterations of the risk assessment can be performed and as information increases in quantity and quality – the risk estimate will improve as well

Risk estimates do provide information on relative magnitude of risk for risk management purposes