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The Role of Analytics in the Development of Advanced Process Controls (APC)Patrick Swann, Ph.D.September 6, 2016


Specifications are “one part” of an overall Control Strategy


APC can enable an Attribute-Based Control Strategy

Improved use of analytics allows focus on specific quality attributes in-process and use of known levers for process controlAn attribute-targeted control strategy using APC can lead to more efficient and effective controlsMore efficient controls can improve availabilityMore effective controls can improve quality assurance


Product Complexity


Traditional Approach - Charge VariantsIEC

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Minutes6.00 6.10 6.20 6.30 6.40 6.50 6.60 6.70 6.80 6.90 7.00 7.10 7.20 7.30 7.40 7.50 7.60 7.70 7.80 7.90 8.00 8.10 8.20 8.30 8.40 8.50 8.60 8.70 8.80 8.90

Acidic isoforms

Main isoforms

Basic isoforms

Marker

Imaging Capillary IEF of an IgG1 Monoclonal Antibody

cIEF

Slide courtesy of Li Zang, Biogen Analytical Development


Product Characterization - Acidic Fraction Collection

• Free Flow Electrophoresis

IEF based separation, direct correlation of fractions with cIEF peaks

• Fractionation of monoclonal antibody acidic species into 3-4 sub-species

6 http://www.ffeservice.com/index.php/technology.htmlSlide courtesy of Li Zang, Biogen Analytical Development


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Acidic Fractions Collected by FFE

DSMain peakAcidic fraction 1Acidic fraction 2Acidic fraction 3Acidic fraction 4



Asparagine Deamidation

1 2 3 4

N287 0.4% 0.1% 0.2% 0.6% 1.2% 1.2%

N316 2.8% 0.7% 2.7% 6.1% 7.2% 7.6%

N362 0.1% 0.1% 0.1% 0.2% 0.2% 0.2%

N385, N390 4.6% 1.4% 1.8% 8.5% 8.1% 8.5%

Trend

Heavy Chain

Acidic FractionsDS

Main Peak

DeamidationChain

DS



Isoforms DS Main Peak Acidic Fractions1 2 3 4

Light ChainCML (+ 58 Da) ND ND ND 0.4% 0.7% 1.0%Glycation (+162 Da) 0.6% 1.1% 0.6% 1.1% 0.7% 3.2%N-Glucuronyl (+176 Da) 0.4% ND 0.3% 1.0% 1.0% 0.3%

Heavy Chain

CML (+ 58 Da) 1.2% ND 1.4% 2.9% 3.9% 3.6%+ 79-90 Da 0.8% ND 0.5% 1.5% ND ND+ 111-116 Da 0.6% ND 0.6% ND 1.8% ND+ 121-123 Da ND ND ND 0.7% ND ND+ 132 -137 Da 0.6% ND ND ND 1.1% 0.9%Glycation (+162 Da) 3.1% 1.9% 4.1% 3.1% 3.3% 3.0%N-Glucuronyl (+176 Da) 1.1% ND 1.2% 7.2% 7.2% 7.6%Total impurity 6.4% 3.0% 8.7% 17.9% 19.7% 19.6%

Impurity Level by Reduced Intact Mass


Published in: David R. Bush; Li Zang; Arseniy M. Belov; Alexander R. Ivanov; Barry L. Karger; Anal. Chem. 2016, 88, 1138-1146.DOI: 10.1021/acs.analchem.5b03218Copyright © 2015 American Chemical Society


Protein Modifications in Acidic Species

Ref: Du, Y., et al. "Chromatographic analysis of the acidic and basic species of recombinant monoclonal antibodies." MAbs 4(5).


PTM complexity at individual amino acid level >> separatory capability

An attribute-based control strategy can leverage chemical knowledge about factors that cause formation of these modifications Y = f(x)


The way forward


Biotech Manufacture – High Level Model

Product Quality

Process Input

Proc

ess

Process Control • Robust process design • Advanced process control

Raw Material

RM Control• Screening and/or • Control by Vendor• Learn from MFG experience


APC Key Concepts

Process Analytical TechnologyA system for designing, analyzing, and controlling manufacturing through timely

measurements (i.e., during processing)

of critical quality and performance

attributes of raw and in-process materials

and processes with the goal of ensuring

final product quality.

At-line

In-line

On-line

Slide courtesy of Bassam Nakhle, Biogen Analytical Development


APC Key Concepts

DS DP

Real Time Release Testing (RTRT)The ability to evaluate and ensure the quality of in-process and/or final product based on process data, which typically include a valid combination of measured material attributes and process controls.

Slide courtesy of Bassam Nakhle, Biogen Analytical Development


APC applied to Biotech Manufacture


15kL3750L950L

Seed train

Production Reactor HarvestRaw

MaterialsPurification Filling

DS R

elease

DS• Endotoxin• Bioburden• Potency

APC for Biotech Drug Substance

In-line: protein concentrationAt line: purity, aggregation,

charge variants

Raw Materials• Geneology• Spectroscopic tools• Rapid ID testing

Media/buffer Prep control

UF/DF: in-line Protein concentration

Bioreactor: in-line Raman, capacitance

feedback feedback

Feed forward

Bioreactor and/or harvest:At line multi-attribute testing and/or CQA Predictive models for feedforward control

http://www.google.com/url?sa=i&rct=j&q=&esrc=s&source=images&cd=&cad=rja&uact=8&ved=0ahUKEwjIs9j4sbPKAhXLbT4KHV6XBJUQjRwIBw&url=http://mohali.all.biz/mixing-tank-g343888&psig=AFQjCNF-pMkbyVtS0dboSv-LQTcefVIEig&ust=1453207500280756

http://www.google.com/url?sa=i&rct=j&q=&esrc=s&source=images&cd=&cad=rja&uact=8&ved=0ahUKEwjIs9j4sbPKAhXLbT4KHV6XBJUQjRwIBw&url=http://mohali.all.biz/mixing-tank-g343888&psig=AFQjCNF-pMkbyVtS0dboSv-LQTcefVIEig&ust=1453207500280756


Bioreactor Capture Polish 1 Polish 2 DrugSub.

Drug Prod.

Sialic acid

Deamid-ation

Trisulfidebonds

High mannose

Glycation

AGE

Fragments

Met X oxidation

Etc….

Critical Control Point - a step at which control can be applied and is essential to prevent or eliminate a hazard or reduce it to an acceptable level (ASTM E2590).

Possible Control Points for Charge-Related Attributes


High-Throughput Peptide Map Workflow

30min gradient

Pepfinder, automatic peptide identification

1 2

34

Targeted peptide quantitation

Bravo ProA purification (60 min/batch)

Lys-C digestion or rapid trypsin digestion (1-2 hr)

LC –MS analysis, 30 min/sample

Data analysis, 0.5 hr/sample

In-house writtenExcel Script

50-100 µg protein digest

Slide courtesy of Zoran Sosic, Biogen Analytical Development


2-AA analysis (routine)

Peptide Mapping

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BiN

A0

BiN

A0-

Gal

BiN

A0-

2Gal

Mon

osia

lylg

lyca

ns

Correlation of %Galactosylation with 2-AA

Slide courtesy of Zoran Sosic, Biogen Analytical Development


Controlling Glycation via Glucose

21

Low glucose feedback control

High glucose feedback control

Slide – JP Smelko. Data courtesy of Brandon Berry and Terrence Dobrowsky

Glycation = f ([glucose], time, …)


Summary & ConclusionsWhen product complexity is greater than analytical specificity, end-product testing alone is not an attribute-based control strategy

High throughput and selective methods applied to process intermediates can improve process understanding

This process understanding allows a focus on known “levers” (critical control points and critical process parameters) for more efficient and effective controls of product quality attributes

Attribute = f (x1, x2 ,…)


AcknowledgementsRohin Mhatre – Regulatory Affairs

Brian Fahie – Analytical Development• Li Zang• Zoran Sosic• Bassam Nakhle

Eliana D. Clark – Manufacturing Sciences

John Paul Smelko – Cell Culture Development

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The Role of Analytics in the Development of Advanced ...c.ymcdn.com/sites/ · The Role of Analytics in the Development of Advanced Process Controls (APC) ... during processing )