The biological activity assay: Key role in QbD approach

MSc Lisel Viña, 2015
The biological activity assay:
Key role in QbD approach

The biological activity assay: Key role in the QbD approach
Ideas around a proposal
• Low translational efficiency from pharmaceutical science to
industry
• QbD as part of solution
• Criticality of quality attributes: Correlation with clinical
outcome?
• Limitations of preclinical studies
• Opportunities from Biological activity assay
• Challenges of correlation studies in cancer immunotherapy
settings
• CimaVax-EGF: Model for a proposal

Pharma translational efficiency
Many years are employed to approve a new drug
Many tested drugs never arrive at the end
This inefficiency is propagated to the approved drugs prices
Less drugs at higher cost!

Some other reasons
… pharmaceutical companies have believed in product
innovation rather than process innovation
Girish Malhotra. Pharmaceutical Costs, Technology Innovation, Opportunities & Reality.
February 2010.
The National Institutes of Health (NIH) focus on innovative
biomedical science, not the applied science of the
development process
Janet Woodcock et al. The FDA Critical Path Initiative and Its Influence on New Drug
Development. Annu. Rev. Med. 2008.59:1-12.

In fact, the industry’s hyperfocus on (regulatory)
compliance is often an obstacle to quality.
Daniel Matlis. Is Compliance an Obstacle to Quality?Life-Science Panorama. Posted on
April 14th, 2014
We have an industry which currently does not understand
many of its basic process sufficiently to be able to control
them in-line.
Gawayne Mahboubian-Jones. Arrogance, Ignorance, and Fear: Too Much for QbD to
Overcome?Posted on 20 August 2010 en PharmaQbD

QbD has promised a new way to go to the
market.
How QbD will do that?
It will not due going to market faster (or cheaper).
QbD is about getting to market reliably.

QbD: Decision are based in knowledge according to predefined
objectives
Direction of the design:
From clinical desired outcome to process

Traditional development
(QbA)
Advanced development (QbD)
Specification
s
Based in process results of
few initial batches, at low
scale at the registration
moment
Based in understanding of MoA and functional
relations
Process Inflexible and static
Ranges of parameters
operations based in results of
few initial batches.
Validation at the beginning
Risk analysis, defined criticality of process
parameters with scientific and technical sound.
Adjusted to design space.
Validation with Life cycle approach
Control
strategy
Retrospective analysis
Process consistency
Analysis off-line
Non understood variability
Prospective analysis
Statistical control of critical process parameters
PAT
Predicted quality
Studied Variability and understood
causality
Life cycle
managment
Reactive Preventive
Continue improvement
QbT: Quality by Analysis

Assessing criticality
• How to assess the criticality of process
parameters and quality attributes of
products which define clinical outcome?
• How to set acceptance criteria and limits
of specifications?
• Without knowledge about the potential
impact on the final patient any decision
about this is almost arbitrary

Clinical
outcome
Product attributes
Process parameters
Identify Criticality for Clinic outcome: Key role in the QbD approach
How to convert theory in practice?
Preclinical
trial
Is it possible to correlate quality
attributes with clinical outcome?

Preclinical studies
Many researchs report low rates of clinically predictive
preclinical studies
• As preclinical models have to recapitulate natural
human disease, it is difficult to find relevant animal
models
• The predictive value of some preclinical studies
was obscured by inclusion of poorly designed and
executed preclinical studies1
• Low reproducibility of the results2
1. Henderson et al. A meta-analysis of threats to valid clinical inference in preclinical research of
Sunitinib.. eLife 2015
2. C. Glenn Begley. An Unappreciated Challenge to Oncology Drug Discovery:Pitfalls in Preclinical
Research. 2013 ASCO EDUCATIONAL BOOK |

Clinical
outcome
Product attributes
Process parameters
Identify Criticality for Clinic outcome: Key role in the QbD approach
How to convert theory in practice?
Is it possible to correlate quality
attributes with clinical outcome?
Biological
activity assay

Looking for experiences of BAA and clinical
outcome correlations
• Many authors and guidelines refer the possibility
and even the necessity but…
– Almost absent in scientific papers
– The most of authors are limited to explain it
based in risk assessment and theoretical
considerations
– There is an abysm between producers-quality
staff and clinicians
• More close experience: IVIVC (test dissolution
and PK studies)

Advantages of Biological Activity Assays
(BAA)
• They are a correlate of biological activity
but do not necessarily reflect the
mechanism of protection in human
• They are much more
simpler,
cheaper,
less time consuming and
reproducible

Is it possible to development BAA enough
specific to detect molecular variants of products?
Poster 87. Stability-indicating profile of a humanized IgG1 monoclonal antibody:
potential applicability of bioassays. Mercedes Cedeño et al. CIM. BioMIT-2015
Size exclusion chromatography SDS-PAGE
The answers is YES!
Stability profile of IgG1 humanized mAb at 2-8°C.

Two BAA were able to detected them
Poster 87. Stability-indicating profile of a humanized IgG1 monoclonal antibody:
potential applicability of bioassays. Mercedes Cedeño et al. CIM. BioMIT-2015
Colorimetric in vitro cell-based
potency assay
Fluorescence intensity MFI
Flow Cytometry
Twenty four-month stability profile of IgG1 humanized mAb at 2-8°C.
BAA is enough robust and reproducible

Xiaoyi Yang, et al. Biopharmaceutical Development Program, SAIC-Frederick, Inc., Frederick National Laboratory
for Cancer Research, Frederick, MD, 21702

Inter- and Intratumor !!
Tumor Molecular Heterogeneity
RAS EGFR MYC MET
Patient Heterogeneity
Challenges of correlation
studies
in cancer immunotherapy
settings

Challenges of correlation studies
in cancer immunotherapy settings
• Clinical trials are design to evaluate
– safety and “proof of concept”
but are not designed to
– determine critical quality attributes and according to
emerging concept of “Space of design”
• Clinical trial design use just a few batches
• Cancer treatments are administrated several times
during life and the same patient receive several batches
making difficult traceability effects of batch.

Biomarkers, personalized medicines and
prediction
.
• The current problems with predicting and evaluating drug
efficacy could also be decreased by using biomarkers.
• New biomarkers can
_ improve diagnosis,
_ define disease subsets that may differ in response,
_ define individual variability in the drug’s molecular target,
_ And provide an early readout of response to therapy.
But investigational drugs are rarely developed in concert with
new diagnostic tests.
The FDA Critical Path Initiative and Its Influence on New Drug Development∗
JanetWoodcock1 and Raymond Woosley2. Annu. Rev. Med. 2008.59:1-12.

Quantitative
BAA
Patient variability Biomarkers
Immune system senescence
Molecular
variants
Tumor variability Biomarker
• Ligand dependent growth
Able to
detect
Biomarker as surrogate of
response
Define subset of
disease
Define individual
variability
Early and
quantitative readout
of response to
therapy
Isolate variability sources
of the response
To control this variables allow increase sensitivity of
statistical test to asses impact of batch to batch variation
Biomarkers and
Personalized medicine
A cancer vaccine project to asses criticality of products attributes and process parameters
Poster 83

CimaVax-EGF: Model for a proposal
NSCL cancer vaccine
Vaccinated
Control
Antibody titers and EGF concentration
are inversely correlated
Xitlally Popa Navarro. 5th Global Meeting
EGF Vaccine. 2015.
Induction

EGF serum level
Surrogate response Biomarker
Danay Saavedra Xitlally Popa Navarro.
5th International Meeting CimaVax-EGF. 2015.
Basal EGF serum level as predictive
response biomarker
Tumor variability Biomarker
Some Tumors are dependent of EGF
EGF serum level correlate
with survival

Biomarkers of immune system
senescence
Danay Saavedra 5th International Meeting CimaVax-EGF. 2015.
Patient variability
Biomarkers

Correlation study
Molecular
variants
Quantitative Biological
activity
(Immunogenicity assay)
Clinical
outcome
(EGF serum
concentration
as surrogate)
Figura 2. Perfil
0.0 5.0 10.0 15.0 min
0.00
0.25
0.50
0.75
1.00
1.25
(x100,000)
EGF serum level
Poster 83

Statistical model
Dependent Variable:
Y: patient response (Predictor of response biomarker)
Independent Variables (controlled but not previously fixed):
X1: Batch potency
X2…Xk: Other quality products attributes
Z1: Tumor variability biomarker or Basal EGF Concentration
(categorical)
Z2: Patient variability biomarker or Immune system senesce
(categorical)

Practical aspects
• Each patient will use only one batch of
vaccine during induction phase
• The 3 kind of biomarkers will be tested for
each patient

• Data base should be
constructed to facilitate
statistical evaluation
Multidisciplinary team should participate in project organization, collection
and analysis data (Project management, clinical, quality and production)
Source: Roudier, B. 2015

Change of paradigm
• Guidance for Industry
• Potency Tests for Cellular and Gene
Therapy Products
• DRAFT GUIDANCE
• Guidance for Industry
* Not to close specification range so quickly
and without enough rationale!
Potency Tests for Cellular and Gene Therapy Products. DRAFT GUIDANCE. 2008
Traditional drug development QbD approach for drug development
BAA is a measurement of process
consistency and correlation is
theoretically assumed
Define BAA as surrogate of clinical
outcome
Specifications are fixed inside boundaries
of lots used in the pivotal clinical studies
demonstrating clinical effectiveness1
Specifications can be modified any time
after asses impact in clinical outcome
through BAA correlation with product
quality attributes
*

Clinical
outcome
(Biomarker
Surrogate of
response)
Preclinical
trial
Biological
activity assay
Product attributes
Correlation
First stage?
Assumed Correlation
Potency assay
Process parameters
Correlation second stage
Correlation
third stage
Potency assay validated for Third stage (No more clinical trials): Needed for
comparability studies

My proposal
• Develop strong ability and capacity to design biological
activity assays
• Develop strong analytical capacity to measure products
trough the whole process
• Design and organize the clinical trial able to trace batch to
batch variability effect in patients
• Design a database and record relevant data across the entire
development process (production, quality, preclinical, clinical)
• Correlate QA and PP, BAA, and surrogate response
biomarker controlling other biomarkers of patient variability
and disease subsets with multivariate statistical tools
• Use BAA as surrogate of clinical outcome when finish the
clinical trial or when test molecular variants and process
changes

There is a lot of resistance and doubts
• All this effort is time consuming, maybe
expensive and even with some ethical
commitment but more time consuming,
expensive and ethically unacceptable it is
not to know
• To do it better, researchers, clinicians and
technologists have a long walk to have
together

Thanks!
Staff from Quality
Joaquín Solozabal
Mercedes Cedeño
Loany Calvo
Staff working with CimaVax-EGF project
Grisel Rodríguez
Liset Sánchez
Danais Saavedra
Xitlialy Popa
Dr. Agustín Lage
Thanks for your attention!
Specially to all of them than
encourage and help me to follow this
idea

The biological activity assay: Key role in QbD approach

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