case study of prior knowledge: development and ......repeatability < 10% cv < 20% cv linearity...

Case Study of Prior Knowledge: Development

and Implementation of a Binding Assay to

Assess the Potency of Synagis® (palivizumab)

Mark A. Schenerman, Ph.D.CASSS Netherlands Discussion Group

April, 2018

Outline

• What is prior knowledge?

• Mechanism and epidemiology of RSV disease

• What is Synagis® and how does it prevent RSV disease?

• Potency assay assessment

• Use of the F protein binding ELISA

• How can prior knowledge be used for ”next generation” products?

2

What is Prior Knowledge?

Overall Knowledge

Published literature

Non-clinical

information

Clinical information

3

Influence of Prior Knowledge

Sponsor’s clinical

experience

Published clinical experience

Sponsor’s pre-clinical experience

Published pre-clinical experience

Published literature*

4

Most

influential

Least

influential*for example, manufacturing/QC publication from

another company

Credibility Index

Peer-reviewed published

papers

QA-reviewed company reports

Witnessed lab notebooks

Trade journal articles*

5

*not peer-reviewed

Most

credible

Least

credible

Respiratory Syncytial Virus (RSV)

• Isolated in 1956

• Orthopneumovirus family (ssRNA viruses)

• Most important viral agent of serious

respiratory tract disease in the pediatric

population

• No fully effective anti-viral therapy or

approved vaccine

6

Orthopneumovirus Structure

7

RSV Life Cycle

8

Mab Binding to F Protein Antigen

9

WHO meeting on RSV in High Risk Infants (2016)

https://www.google.com/url?sa=t&rct=j&q=&esrc=s&source=web&cd=3&cad=rja&uact=8&ved=0ahUKEwjp0I3I0sfWAhWD4

SYKHVhoAgYQFggxMAI&url=http%3A%2F%2Fwww.health.gov.on.ca%2Fen%2Fpro%2Fprograms%2Fdrugs%2Ffunded_d

rug%2Ffund_respiratory.aspx&usg=AFQjCNFaRMvg1nUc5nV_QUIJgnBc4CMM1g

RSV Prophylaxis

• Anti-viral therapies and vaccines are not

currently an effective option for infants at risk

of infection

• Passive immunotherapy using intravenous

immune globulins has proven to be safe and

effective (RespiGam®)

• Passive immunotherapy using monoclonal

antibody (Synagis®--palivizumab) at a

reduced dose has proven to be safe and

effective

10

Synagis® (palivizumab)

• Humanized monoclonal antibody (MAb)

• Launched September 1998

• Prevention of serious lower respiratory tract disease caused by RSV in high risk infants

• 300,000+ infants annually in U.S.

11

Why is Synagis® Important?

• RSV is the most common cause of lower

respiratory infections in infants and children

worldwide (estimated 3.4 million episodes of

severe RSV infection resulting in hospital

admission)

• Each year in the United States, more than

90,000 infants are hospitalized with RSV

disease

• There are approximately 325,000 infants at

high risk of acquiring severe RSV disease in

the U.S. 12

Assays for Potency

• Microneutralization

• F protein binding ELISA

• Fusion inhibition

• Cotton rat prophylaxis

14

Binding Assay Used for Potency Test?

• Mechanism of action is well-established* (preclinical)

• Development of animal models, cell culture based

assays, and binding assays (preclinical)

• Accelerated stability studies show parallel or

comparable results (preclinical)

• Clinical data shows no significant adverse events

(clinical)

• Parallel real-time stability data shows no adverse

trends (clinical)

• Continue monitoring animal models/bioassays as a

characterization test (marketed product)

15

*Collins, PL, Chanock, RM, and Murphy, BR. (2001) in Fields Virology

Volume 1, 4th edition, Lippincott, Williams, and Wilkins, Philadelphia, pp.

1443-1485.

Mechanism of Action

• Binding to the F protein (specific neutralizing epitope) on the surface of the virion

• Glycosylation of the antibody plays no significant role

• Complement plays no significant role

• Molar equivalent of Fab has comparable binding

• Fc region plays no significant role in potency of antibody

16

Effects of DeglycosylationSample

Description

F protein ELISA

(% of Reference

Standard)

Microneutralization

(ED50 of

sample/ED50 of

Ref. Std.)

PNGase treated

Ref. Std.*

93% 0.76

Reference

Standard

Control

95% 1.13

17

*Reference Standard lot was digested with PNGase (8 Units of enzyme per mg of Synagis) for 22 hours at 37C. The control

digestion was performed under identical conditions without enzyme. The completeness of digestion was monitored by observing a

shift in molecular weight of the heavy chain on SDS-PAGE and CGE.

Effect of Complement

0

20

40

60

80

100

120

140

% o

f R

ef. S

td. E

D50 (

ng

/ml)

Reference Standard

RS + rabbit complement(neat)

RS + rabbit complement (1:2)




RS + rabbit complement(1:10)

18

• Complement has no effect on neutralization

Accelerated Stability

• F protein ELISA and microneutralizationshowed parallel trends (no significant decline)

• HPSEC showed significant decrease

• Potency assays may not be as sensitive an indicator of stability as biochemical tests

• Rate of decline for assays is product-and assay-specific

19

Accelerated Stability of Synagis®

50

70

90

110

130

150

170

190

% o

f R

ef.

Std

.

ELISA MNT

Months at 40C

0

1 month

2 months

3 months

6 months

20

• Neither assay showed significant change during accelerated

stability

Red bars indicate 95% confidence intervals.

Real-time vs. Accelerated Stability

21

60

70

80

90

100

110

120

130

140

0 10 20 30 40 50

Months of storage

% o

f R

ef.

Std

.

HPSEC (2-8C)

HPSEC (40C)

ELISA (2-8C)

ELISA (40C)

• HPSEC showed significant change during

accelerated stability but ELISA did not

Similar Clinical Results Between Lots

• Multiple lots (> 12) from different scales made

at different locations showed comparable

animal and human PK results

• Real-time stability data on multiple lots

showed no significant differences

• If clinical lots showed differences, these

would need to be discussed with the

regulatory authorities because binding alone

might not be detecting the changes

22

Cotton Rat Prophylaxis

0

0.5

1

1.5

2

2.5

3

Lo

g r

edu

ctio

n o

f R

SV

2.5 mg/kg 1.0 mg/kg 0.4 mg/kg

Dose

Ref. Std.

Lot 1

Lot 2

Lot 3

23

• No difference in potency in animals using

different batches

Human PK

24

3 MG/KG MEAN SERUM LEVELS

1

10

100

0.0

0

0.2

5

0.5

0

1.0

0

4.0

0

8.0

0

12.0

0

1.0

0

2.0

0

3.0

0

4.0

0

5.0

0

7.0

0

14.0

0

21.0

0

30.0

0

37.0

0

60.0

0

HOURS DAYS

TIME

SE

RU

M L

EV

EL (

MC

G/M

L)

15 MG/KG MEAN SERUM LEVELS AND STANDARD ERRORS

1

10

100

1000

-1.00

0.00

0.25

0.50

1.00

4.00

8.00

12.00

1.00

2.00

3.00

4.00

5.00

7.00

14.00

21.00

30.00

60.00

HOURS DAYS

T IM E

15 MG/KG LIQ IV

15 MG/KG LYO IV

3 mg/kg IM15 mg/kg IV

• No difference in human PK, regardless of dose or

method of administration

Validation Comparisons

Parameter ELISA Microneut.

Repeatability < 10% CV < 20% CV

Linearity > 0.990 > 0.970

Selectivity Specific for

Synagis

Specific for

Synagis

Intermediate

precision

< 20% CV < 30% CV

Robustness < 20% CV < 30% CV

25

Conclusions

• Synagis® potency assay developed based on understanding of the mechanism, effectiveness of passive immunotherapy, and parallel stability data

• All results suggested that Fc function played no significant role in product potency

• Microneutralization and F protein binding ELISA behaved the same during accelerated and real-time stability testing over multiple lots

• F protein binding ELISA could be used for potency testing

26

Application of Prior

Knowledge to New Products

• Understanding of mechanism of action (MoA) can

enable faster development of next generation

products

– Must demonstrate same MoA in new product

• Simplified control strategy may be achieved sooner, if

product is in the same class (e.g., monoclonal

antibody)

• For antibodies that have more complex mechanisms

of action, using binding assays as the sole measure

of potency may not be suitable

27

Acknowledgements (MedImmune)

• Bob Strouse, Sheau-Chiann Wang, Tony DeFusco, and Fadi Hakki (Analytical Dev.)

• Gail Folena-Wasserman (Development)

• Julie Lanahan (QC)

• Dave Pfarr (Research)

• Julia Goldstein (Regulatory)

• Franco Piazza (Clinical)

• Filip Dubovsky (Clinical)

28

Johns Hopkins University (JHU) proposal to study

correlation between quality data and

immunogenicity

• Mark Schenerman, Ph.D.

President, CMC Biotech-MAS Consulting

Confidential information

30 June 2017

CONFIDENTIAL – DO NOT DISTRIBUTE

Monoclonal dimer levels have no significant

correlation with patient immunogenicity

Hypothesis

3

0

Principle Investigator

Caleb Alexander,Associate Professor

John Hopkins UniversityBloomberg School of Public Health

Departmental Affiliations•Epidemiology (Primary)

•Division: Cardiovascular Disease and Clinical Epidemiology•School of Medicine (Joint)

Center & Institute Affiliations•Center for Drug Safety and Effectiveness•Center for Health Services and Outcomes Research•Center for Mental Health and Addiction Policy Research•Center of Excellence in Regulatory Science and Innovation (CERSI)

http://www.jhsph.edu/departments/epidemiology/

http://www.jhsph.edu/research/centers-and-institutes/center-for-drug-safety-and-effectiveness/index.html

http://www.jhsph.edu/research/centers-and-institutes/health-services-outcomes-research/

http://www.jhsph.edu/research/centers-and-institutes/center-for-mental-health-and-addiction-policy-research/

http://www.jhsph.edu/research/centers-and-institutes/center-of-excellence-in-regulatory-science-and-innovation/


• Assemble product quality (dimer levels) and clinical safety

(immunogenicity) data on monoclonal antibodies to either

prove or disprove the hypothesis (see mock database slide)

–Data includes different monoclonal antibodies that are

IgG1, IgG2, or IgG4 isotypes and have been evaluated in

the clinic (Phase 2-3)

• Database is owned by JHU (or CERSI)

• Solicit other monoclonal manufacturers to contribute data

• Sponsors would anonymize the data (lot numbers) so it

could be publically studied for trends

How will the study be done?


• Proprietary information will be protected by JHU

• Only JHU will know the identities of the companies that participate;

sponsors must give permission to be named in public presentations

• Database will eventually have a public-facing view so that other global

epidemiologists can analyze the data

Data compilation by JHU


• JHU epidemiologists at the Bloomberg School of Public Health will

analyze the data for trends in safety (immunogenicity)

• Through the collaborative interaction with industry sponsors, various

sub-set analyses may be performed based on patient population,

indication, and Ig subtype.

• Findings will be published in a high impact journal (e.g., Nature)

Data analysis by JHU Epidemiologist (Caleb Alexander)


• Builds industry collaboration with a world renowned epidemiology

group at JHU

• JHU group lends credibility to the study; makes subsequent

publication more impactful

• JHU group is part of joint FDA/JHU foundation (CERSI) that is

dedicated to product safety monitoring

• Delivers on the challenge presented by regulators to analyze and

correlate quality and safety data

Benefits of the Study


• New safety signal identified through the study; would need to be

reported to regulators

Risks


• Opens the opportunity for discussion with regulators whether dimer

could be considered less risk (non-CQA)

• May enable greater manufacturing flexibility, while maintaining

appropriate control of all aggregates

• Science-driven approach to challenging the Health Authority

stereotype that “all aggregates are a high risk of immunogenicity”

Possible outcomes 1

Hypothesis is proven


• Maintains current state

• All aggregates considered to be the highest immunogenicity risk

• No change to current approach to process development or product

control

Possible outcomes 2

Hypothesis is disproven


• Maintains current state

• All aggregates considered to be the highest immunogenicity risk

• No change to current approach to process development or product

control

Possible outcomes 3

No clear conclusion


What is the Center for Regulatory Science & Innovation (CERSI)?

• FDA's Centers of Excellence in Regulatory Science and Innovation (CERSIs) are collaborations

between FDA and academic institutions to advance regulatory science through innovative

research, education, and scientific exchanges. Evolving areas of science are promising new

approaches to improving our health while demanding new ways to evaluate the safety and

effectiveness of the products FDA regulates. FDA’s Strategic Plan for Advancing Regulatory

Science describes how FDA is harnessing these new technologies in collaboration with

academia, industry, and other governmental agencies to develop the tools, standards, and

approaches required to assess the safety, efficacy, quality, and performance of innovative

products.

• CERSI centers:

–University of Maryland

–Georgetown University

–University of California at San Francisco (UCSF) in a joint effort with Stanford University

(UCSF-Stanford)

–Johns Hopkins University

–Yale University in joint effort with Mayo Clinic

• https://www.fda.gov/ScienceResearch/SpecialTopics/RegulatoryScience/ucm301667.htm

https://www.fda.gov/ScienceResearch/SpecialTopics/RegulatoryScience/ucm301667.htm

case study of prior knowledge: development and ......repeatability < 10% cv < 20% cv linearity...

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