Microbial Testing of Cell Therapy Products Summary of NIH Clinical Center Studies

1. 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

2. 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

3. 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

4. Both BacT/Alert and Bactec were superior to CFR in overall organism detection N=6x3x2=36; except AN, n=28

5. 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

6. Multiple antibiotics in product medium impaired detection of organisms in all systems N=10x3x2=60

7. 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

8. 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

9. 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

10. 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

11. Parallel Study: Results by Product Category

12. Parallel Study: Results by Product Category

13. Parallel Study: Results by Product Category

14. 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

15. 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