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Nov 09, 2022 234 likes •493 views

Evaluation of immunogenicity of pharmaceuticals Geoff Hale Chief Executive Officer BioAnaLab Limited Professor of Therapeutic Immunology Oxford University Guideline on Immunogenicity Assessment of Therapeutic Proteins.

SLIDE 1

Evaluation of immunogenicity

f pharmaceuticals

Geoff Hale

Chief Executive Officer BioAnaLab Limited Professor of Therapeutic Immunology Oxford University

SLIDE 2

Guideline on Immunogenicity Assessment of Therapeutic Proteins. EMEA/CHMP/BWMP/14327/2006 Mire-Sluis AR, Barrett YC, Devanarayan V et al. (2003) Recommendations for the design and

ptimization of immunoassays used in the

detection of host antibodies against biotechnology products.

J. Immunol. Meth. 2004; 289:1-16.

SLIDE 3

Principles

Primary concern is clinical sequelae
Assessment requires appropriate assays
Wide range of technical difficulties
Immunogenicity assays are quasi-

quantitative due to lack of reference

Titre-based approach is preferred
Recommendations are based on experience

and not a substitute for regulatory guidance

r intended to stifle innovation.

SLIDE 4

Topics

Cut point and assay sensitivity
Quantitation
Confirmatory Assays
Validation.

SLIDE 5

0.0 0.2 0.4 0.6 0.8 1.0 1.2 1.4 1.6 1 10 100 1000 Concentration (ng/ml) Optical Density

Binding to CD52 antigen (Antagonist effect)

Campath Glyco1

SLIDE 6

Cell-Mediated killing (ADCC) (Agonist effect)

0.01 0.1 1 10 100 1000 Concentration (ng/ml) 20 40 60 80 100 Specific cell killing (%) Campath Glyco1

SLIDE 7

Screening Assay – Cut Point and Sensitivity

The cut point will be 1.645 SD above the mean “It is appropriate to have 5% false positives” “Detection of some false positive results is inevitable” “eg 3SD above background” Sensitivity must be less than 500 ng/ml and the lower the better “Strive for sensitivities near 250 to 500 ng/mL” “Capable of detecting antibodies in all antibody-positive samples/patients”

Clients Mire-Sluis EMEA

SLIDE 8

The following slides illustrate the effect of different levels of biological variability (Bio SD) and analytical variability (Assay SD) on the determination of “positive” samples, using sets of normally-distributed random data. It is shown that even a small level of assay variability can lead to highly non-reproducible results and when the assay variability is comparable with the biologic variability, the cut-point methodology proposed by Mire-Sluis has no useful value.

SLIDE 9

Bio SD=0.00 Assay SD=0.02

0.000 0.020 0.040 0.060 0.080 0.100 0.120 0.140 0.160 5 10 15 20

Serum number Response (AU)

SLIDE 10

Bio SD=0.02 Assay SD=0.01

0.000 0.020 0.040 0.060 0.080 0.100 0.120 0.140 0.160 5 10 15 20

Serum number Response (AU)

SLIDE 11

0.000 0.020 0.040 0.060 0.080 0.100 0.120 0.140 0.160 5 10 15 20

Serum number Response (AU)

Bio SD=0.02 Assay SD=0.005

SLIDE 12

Cut Point and Sensitivity

a case for “case by case”

Consider:

Clinical consequences of antibodies
Therapeutic concentrations of drug
Likely frequency of antibodies
Biosimilars – similar assay or not?

SLIDE 13

Quantitation of Response

Often require calibration curves and QC samples with same acceptance criteria as

ther ligand-binding

assays “Due to the quasi- quantitative nature of immunogenicity assays, we advocate a titer-based approach” “(Positive) samples need to be characterised in terms

f antibody content

(concentration/titre)”

Clients Mire-Sluis EMEA

SLIDE 14

Confirmatory Assays

Help!! “Immunodepletion assay: a form of confirmatory assay” “Usually advisable to use a different assay format”

Clients Mire-Sluis EMEA

SLIDE 15

Different format?

More sensitive
Why not use as screening assay?
May find positives among control

samples which screened negative

Less sensitive
Fail to confirm true weak positives

SLIDE 16

Same format?

Compare pre and post-treatment
Treatment emergent response
Drug inhibition (immunodepletion)
Drug-specific response

SLIDE 17

The following slides illustrate the effect of small sample size on the results of a confirmatory assay which is evaluated by a simple t-test. There is little difficulty in confirming a strong positve response which Is fully inhibited by addition of drug. However, weak responses may sometimes be confirmed and sometimes not and the result of a particular assay is unpredictable. Improvements in assay precision can even be counter-productive, allowing small differences to falsely appear statistically significant.

SLIDE 18

True positive, confirms treatment-emergent and drug specific

0.000 0.050 0.100 0.150 0.200 0.250 0.300 PRE POST SPIKE

Signal (AU)

SLIDE 19

False positive, confirms negative

0.000 0.050 0.100 0.150 0.200 0.250 0.300 PRE POST SPIKE

Signal (AU)

SLIDE 20

False positive, but confirms treatment-emergent and drug specific

0.000 0.050 0.100 0.150 0.200 0.250 0.300 PRE POST SPIKE

Signal (AU)

SLIDE 21

False positive, but confirms treatment-emergent and drug specific

0.000 0.050 0.100 0.150 0.200 0.250 0.300 PRE POST SPIKE

Signal (AU)

SLIDE 22

Validation

Validation to be completed before starting clinical trials, but guidance needed

n how to do it.

“The validation process will be discussed in a subsequent manuscript” “… ensure all essential procedures are in place before commencement (of the clinical study). This includes … validation of all assays”

Clients Mire-Sluis EMEA

SLIDE 23

Problems with pre-study validation

Lack of suitable positive control
Lack of suitable negative controls
Lack of understanding of potential frequency

and magnitude of responses

SLIDE 24

Pre-validation studies and early phase clinical trials

Demonstrate analytical capabilities using

surrogate reagents

Determine potential analytical range and

acceptance criteria

Carry out in-study validation during Phase I

clinical trials, eg local cut-point with local assessment of sensitivity

Collect samples for positive controls