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Microbial Testing of Cell Therapy Products Summary of NIH Clinical Center Studies. Elizabeth Read MD Chief, Cell Processing Section Department of Transfusion Medicine NIH Clinical Center Bethesda, MD 6/16/06. Study Design & Goals. Seeded Study CFR vs BacT/Alert vs Bactec

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microbial testing of cell therapy products summary of nih clinical center studies

Microbial Testing of Cell Therapy ProductsSummary of NIH Clinical Center Studies

Elizabeth Read MD

Chief, Cell Processing Section

Department of Transfusion Medicine

NIH Clinical Center

Bethesda, MD

6/16/06

study design goals
Study Design & Goals

Seeded Study

CFR

vs BacT/Alert

vs Bactec

Using mock MNC products,

demonstrate that automated

culture methods are

equivalent to CFR method

Khuu et al. Cytotherapy 2004;6:183-195

Parallel Study

CFR vs BacT/Alert

CFR vs Bactec

Using actual cell therapy products,

compare use of automated

culture methods with

CFR method

Khuu et at. Transfusion 2006, in press

seeded study design
Seeded Study: Design
  • Goal: Evaluate organism detection and time to detection
  • Mock mononuclear cell products from leukapheresis
  • 6 commonly used product media
    • Citrated autologous plasma
    • PlasmaLyte A + HSA
    • Freeze mix (DMSO/Pentastarch)
    • RPMI 1640
    • X-VIVO 20 (contains gentamycin)
    • RPMI 1640 w/ multiple antibiotics
  • Each sample seeded with 10 and 50 CFU of 10 different organisms
  • CFR vs BacT/Alert vs Bactec
slide4

Both BacT/Alert and Bactec were superior to CFR in overall organism detection

N=6x3x2=36; except AN, n=28

slide5

CFR/USP

Both BacT/Alert and Bactec were superior to CFR in time to detection

Even for inocula of 10 CFU, time to detection was < 7 days for both BacT/Alert and Bactec (but not for CFR)

BacT/Alert

Bactec

slide7

In medium with multiple antibiotics, impaired detection was variable from one organism to the next

No Growth

SA, YE, BS, AN

No Growth

SA, ML, BS, PB

parallel study design
Parallel Study: Design
  • Goal: evaluate field performance, false positives (true pos evaluation is best done by seeded study)
  • Tested in process and final product samples from real cell therapy products
  • Timeframes
    • 12/1/02 - 5/16/04
      • BacT/Alert vs CFR 1125 samples
    • 5/17/04 – 12/31/05
      • Bactec vs CFR 492 samples
definition of positive results
Definition of positive results
  • Positive results expressed as
    • True positive = detection by system + confirmation by gram stain and/or subculture
    • False positive = detection by system, but could not confirm presence of organisms by gram stain or subculture
parallel study results
Parallel Study: Results
  • True positive
    • Rates comparable for all systems
    • Time to detection: Automated systems were equivalent to, or faster than, CFR/USP
  • False positive
    • High rates (7.1%) with CFR method vs almost none with automated methods (0.2%)
    • Most related to high cell (RBC or WBC) counts in product
slide14
Gram Positive

Staphylococcus epidermidis

Staphylococcus capitis

Staphylococcus, coag negative

Proprionobacterium acnes

Actinomyces spp

Bacillus spp

Corynebacterium spp

Coryneform bacterium

Enterococcus faecalis

Enterococcus spp

Peptostreptococcus

Rothia spp

Staphylococcus aureus

Streptococcus mits

Streptococcus, alpha hemolytic

Streptococcus, Group B

Gram Negative

Pseudomonas fluorescens

Pseudomonas putida

Stenotrophomonas maltophilia

Brevundimonas dimunuta

Bacteroides spp

Proteus mirabilis

Organisms Detected in Cell Therapy Products*(not including pancreas and processed tissue)*most common organisms
do all true positives represent actual product contamination
Do all true positives represent actual product contamination?
  • Highly unlikely, because we are frequently unable to demonstrate organism growth in samples from same product or product derived from same parent product and processed in parallel
  • Given limited volume and number of samples available for a given cell therapy product, this is a problem that is not easily resolved