CHALLENGES AND SOLUTIONS TO RECEPTOR OCCUPANCY STUDIES BY FLOW CYTOMETRY

Transcription

1 CHALLENGES AND SOLUTIONS TO RECEPTOR OCCUPANCY STUDIES BY FLOW CYTOMETRY 4th RSC / DMDG / DMG New Perspectives in DMPK James Munday Science Lead I&I (Harrogate, UK) 21 st -22nd May 2018 Copyright 2018 Covance. All Rights Reserved

2 Agenda 1 Background to the need for Receptor Occupancy (RO) studies 2 Determination of RO by flow cytometry 3 Validation of RO assays Key parameters for a successful validation activity with example case studies 4 Conclusions / Summary 2

3 Background to the Need for Receptor Occupancy Studies 3

4 Importance of Calculating Receptor Occupancy (RO) as Highlighted g by TGN1412 CD28SA (E.g. TGN1412) 1.T-cell Induction of Cytokine release T-Cell CD11b 2.T-cell endothelial cell adhesion Fc R ICAM-1 3 Cytokine Release 3. Endothelial cell damage 4. Organ Failure 4 Data: Covance

5 Importance of Calculating Receptor Occupancy (RO) as Highlighted g by TGN1412 TGN1412 was known to bind nonhuman primate CD28 suggesting that the cynomolgus monkey was an appropriate model However, due to fundamental biologic and pharmacologic differences in monkeys and humans for the TGN1412 target and its downstream effects, the NOAEL dose obtained from monkeys was too high The consequence was that the FIH dose at 0.1 mg/kg was 20- to 30-fold too high; resulting in life-threatening cytokine release syndrome in the healthy volunteers As a result, new guidance from the European Medicines Agency (EMA) recommends selecting a starting dose that would result in a Minimum Anticipated Biologic Effect Level (MABEL) for products in which a potential risk had been identified MABEL calculation is based on a dose dependent curve of drug effect PK/PD model can be constructed to describe a quantitative relationship between drug exposure and RO RO is commonly used as a PD biomarker, especially for cell-surface targeting therapy 5 The TGN1412 case highlights the importance of correctly predicting the MABEL, where reliable PK/PD modelling and the use of RO assessments are fundamental tools

6 Increasing Trend for RO Activities Being Performed Studies Years Trend for Early 2018 Investment to support increase in demand for flow activities 6 Image: Covance Data: Covance

7 Determination of Receptor Occupancy by Flow Cytometry 7

8 CELL Target Receptor Antibody Drug Substance CELL A = determination of free receptors C = determination of Total receptors CELL Excess Antibody Drug substance Labelled Antibody Drug Substance CELL 8 B = determination of Bound receptors Data: Covance D = determination of Background

9 Validating a Receptor Occupation Method Antibody drug substance at , 0.001, 0.1, 0.5, 1.0, 3.0, 7.0, and 10.0 µg/ml Including 0.0 µg/ml (PBS) to simulate pre-dose CELL Target Receptor Antibody Drug Substance 1.20 Receptor occupation Tube A Tube B Tube C Tube D Free Receptors Bound Receptors Total Receptors Background concentration (ug/ml) 9 Image: Covance Data: Covance

10 Calculation of Percent Receptor Occupancy Bound Normalised Tube B Post Dose Tube B Pre Dose Tube C Post Dose Tube B Pre Dose Free Normalised Tube A Post Dose Tube D Post Dose Tube A Pre Dose Tube D PreDose Percentage Receptor Occupancy ( (Bound Normalised) ) (Bound Normalised + Free Normalised) 10 Data: Covance

11 Determination of Bound/Total Receptors with anti-pd1 in Cynomolgus Monkey Serum 11 Data: Covance

12 12 Data: Covance

13 Validation of RO Assays 13

14 Validation of RO Assays CONSIDERATIONS: As with all methods utilized in drug development, validation plans for RO must consider the intended d use of the data and follow a fit-for-purpose approach specific to flow cytometric methods Many factors need to be considered to insure appropriate data interpretation 14

15 Validation Parameters to Consider When Building RO Assays 1. Consistency of results 2. Sample type and storage conditions o 3. Critical reagents 4. Receptor expression 5. Cell population 6. Non-circulating targets 7. Receptor internalisation / shedding 8. Biological i l variability 9. Immunogenicity 10.Test article Mode of action 15

16 Validation of RO Method for Evaluation of Consistency of Results and Storage Conditions Naive Blood Day 0 Prepare blood with TA at titration concentrations Day 0 Run 1 (baseline) Titrations stained Analysed by Analyst 1 on FACS 1 Day 0 Run 2 Titrations stained Analysed by Analyst 1 on FACS 1 Day 0 Run 3 Titrations stained Analysed by Analyst 2 on FACS 1 Residual stained blood analysed Run 1 or Run 2 analysed on FACS 2 Run 1+ Run 2 Compared for intra-assay validation Run 1, Run 2 + Run 3 Compared for inter-assay validation Residual naïve pooled blood stored at 2-8 o C over night Day +1 Prepared titrations stored at 2-8 o C and at room temp over night Naïve Day +1 Prepare blood with TA at titration concentrations Day +1, 2-8 o C Titrations stained Analysed by Analyst 1 on FACS 1 Day +1, RT Titrations stained Analysed by Analyst 1 on FACS 1 Naïve Day +1 Titrations stained Analysed by Analyst 1 on FACS 1 Compared with base line for 2-8 o C stability Compared with base line for RT stability Compared with base line for RT stability 16 Data: Covance

17 Critical Reagents NEED TO CONSIDER FOR ALL REAGENTS DIFFERENCES SPECIFICITY/SELECTIVITY AND AFFINITY Therapeutic Competitive Non-Competitive t e AB 1 AB 2 AB 1 -s-s- -s-s- CH H2 C H 2 AB 2 CH3 C H 3 17 Need to Consider Any MOA that May Affect Interpretation Data: Covance

18 Considerations for Labelling of Critical Reagents How much labelled reagent is required? Avoid multiple labelling if possible Each labelling has a different efficiency Can measure incorporation ratio to normalise data If critical reagents are changed cross validation activities will be required Fluorochrome selection is critical to the success of the RO assay 18

19 Considerations for Cell Population & Receptor Expression CELL POPULATION: Low numbers can make it difficult to measure and may require the implementation of more cell markers RECEPTOR EXPRESSION: Levels of expression can vary between healthy and disease states Receptor can be shed or internalised Expression levels can be variable across species Target may be on non-circulating tissues 19

20 Immunogenicity to Test Article or Critical Reagents MANY FACTORS INFLUENCE IMMUNOGENICITY: Species Related, Product Related, or Environment Related: Glycosylation pattern New disulfide bonds Correctly folded Formulation Aggregation Route of Administration Truncated Dose and length of treatment Oxidation Patient factors: health status, Phosphorylation co-medications, etc Incidence of immunogenicity is typically measured by Anti-Drug Antibody Analysis 20

21 Example of ADA in Study X and How RO Was Used to Interpret Findings INCIDENCE OF ADA IN STUDY X: No ADA detected in majority of high dose animals May indicate drug tolerance constraint for ADA assay 21 Data: Covance ADA detected in majority of animals at low dose

22 RO for treatment groups Control Low Dose High Dose 13 of 15 males and 9 of 15 females show free occupancy <10% 90% receptor occupancy. Therefore, in the majority of animals ADA is not affecting pharmacological activity 22 Data: Covance

23 Future directions with new classes of therapeutic Conventional binary approach to RO: 1 Receptor, 1 Ligand, 1 Cell Type New paradigm to RO: Multiple Receptors, Multiple Ligands and Multiple Cell Types New approaches and technologies applied (e.g. Imaging flow cytometry / High content screening and Different modelling required for defining FIM dose) 23 Data: Covance

24 CONCLUSIONS / SUMMARY Since the TGN1412 clinical trial there has been a growing demand for RO measurements by Flow cytometry to drive MABEL understanding It is important to consider the many parameters that drive understanding of RO and its appropriate calculation For biologics targeting cellular antigens, RO assays are critical measurements As biologics become more complex the challenges of calculating RO will increase and other platform technologies will be required 24

25 Questions? 25

26 Copyright 2018 Covance. All Rights Reserved