The document summarizes challenges and mitigation strategies for high concentration ultrafiltration formulations. It discusses excipient offset effects such as volume exclusion, preferential hydration, and the Donnan effect that can cause excipient concentrations to differ between the diafiltration buffer and final formulation. Two main mitigation strategies are presented: using an offset diafiltration buffer concentration or an averaging strategy where the recovery buffer concentration is adjusted. The document recommends assessing any excipient offsets and their impact on process optimization and protein stability for high concentration formulations.
High concentration UF formulation challenges and mitigation strategies
1. The life science business of Merck KGaA,
Darmstadt, Germany operates as
MilliporeSigma in the U.S. and Canada.
High CONCENTRATION UF
FOrMULATION
CHALLENGES &
MITIGATION STRATEGIEs
Subhasis Banerjee Ph.D.
APAC Bioprocessing Application Lead Expert
Customer Applications, Bioprocessing APAC
Mar 23, 2021
2. The life science business
of Merck KGaA, Darmstadt,
Germany operates as
MilliporeSigma in the U.S.
and Canada
4. Agenda
1
2
3
Why high concentration UF Formulation
Challenges in high concentration UF
Formulation
Theories to explain buffer offsets
4 Mitigation strategies
5. High Concentration UF Formulation Challenges & Mitigation Strategies | 23 Mar 2021
5
Why high concentration UF for mAb formulations
High patient doses required for biological products (mAbs):
~1-3mg/kG (→ up to 10 mg/kg)
Intravenous (IV) infusion – traditional delivery method
Issues: Infusion side effects, cost, quality of life, patient compliance
Subcutaneous administration (Sub-Q) preferred by patients
Ease of Use, savings in time & cost, convenience, mitigate severe after-effects of infusion
Ref: M.Eisenstein, v29 , # 2, Feb. 2011 Nature Biotech
6. 6
Formulation: Excipient offset considerations
Excipient Removal in a Standard (Formulation) UFDF Processes
The goals of a final formulation ultrafiltration/diafiltration
(UFDF) process are:
- Perform a buffer exchange so as to achieve the target product
formulation
- Bring the product to its final concentration
• Target 10 diavolumes for 99.995% removal of the original
buffer replaced by formulated buffer
• Excipients and buffer components typically have no
retention
• Buffer is prepared at the same pH and excipient
concentrations as in the desired final bulk drug substance
% (Rem.Contaminant) = 100* [1-e(R-1)*N]
0.001
0.010
0.100
1.000
10.000
100.000
0 2 4 6 8 10 12
Residual
Buffer
(%)
Diavolumes
Ideal Buffer Exchange
R = 0
99.995% Removal
High Concentration UF Formulation Challenges & Mitigation Strategies | 23 Mar 2021
7. 7
Formulation: Excipient offset considerations
Excipient Removal in High Concentration Buffers
■ Excipient (buffer) concentrations in final bulk have been reported to be different
from diafiltration buffer especially at high protein concentrations
Stoner, M., et al, J Pharm Sciences 2004
High Concentration UF Formulation Challenges & Mitigation Strategies | 23 Mar 2021
9. 9
Formulation: Excipient offset considerations
Volume Exclusion
■ Protein molecules occupy significant volume in solutions at high
concentrations.
Reduces volume available for solutes and solvent which reduces
solvent and solute concentrations on a per volume basis.
Concentrations are equivalent on a molality basis in the absence
of charge effects.
Membrane
P
P
P
P
P
P
VA = VB
NS-A NS-B
Side A Side B
S
S
S
S
S
S
S
S
S
S
S S
S
S
S
S
S
S
S
S
S
S
S
S S
S
S
S
S
S
S
S
S
S
S S
P = Protein
S = Solvent
S = Solute
High Concentration UF Formulation Challenges & Mitigation Strategies | 23 Mar 2021
10. 10
Formulation: Excipient offset considerations
Volume Exclusion
)
1
( pr
pr
DF
R v
c
C
C
Protein B at 100g/L (vpr = 0.72ml/g)
Step
Sorbitol Concentration
(%)
Retentate Pool Average
(4 Runs)
4.1±0.1
DF Buffer 4.5
Model Estimate 4.2
Protein A at 100g/L (vpr = 0.73ml/g)
Step
Sucrose Concentration
(%)
Retentate Pool Average
(8 Runs)
7.6±0.2
DF Buffer 8.5
Model Estimate 7.9
Ref: Maio, F., et al, Biotechnology
Progress 2009
1 2
Estimate volume exclusion effects on
excipient concentration change using:
Model applied to uncharged excipients
for Mab UFDF Process:
where
CR = retentate excipient conc. (mol/L),
CDF = DF excipient conc. (mol/L),
cpr = protein concentration (g/mL), and
vpr = protein partial volume (mL/g)
High Concentration UF Formulation Challenges & Mitigation Strategies | 23 Mar 2021
11. 11
Formulation: Excipient offset considerations
Volume Exclusion
Experimental Data
---- Model
Stoner, M., et al, J Pharm Sciences 2004
Model applied to chloride concentration for net neutral protein
• Evaluated excipient concentration as a function of protein concentration
• CDF = 140mM (NaCl), Vpr= 0.74mL/g
• Model accurately predicts volume exclusion affects for applications with no charge effects or
solute/ion interactions
High Concentration UF Formulation Challenges & Mitigation Strategies | 23 Mar 2021
12. 12
Formulation: Excipient offset considerations
Preferential Hydration
■ Specific and non-specific interactions between solutes and proteins
Solute – Protein Attraction = Solute molality of retentate higher
Solute – Protein Repulsion = Solute molality of retentate lower
Repulsion commonly referred to as preferential hydration
Membrane
P
P
P
P
P
VA = VB
NS-A NS-B
Side A Side B
S
S
S
S
S
S
S
S
S
S
S
S
S
S
S
S
S
S S
S S S
S
S
S
S
S
S
S
S
S
S
S
S
S
P = Protein
S = Solvent
S = Solute
Preferential Hydration Illustration
High Concentration UF Formulation Challenges & Mitigation Strategies | 23 Mar 2021
13. 13
Formulation: Excipient offset considerations
Donnan Effect
■ Occurs when charged species (i.e. Proteins) retained by the semi-permeable
membrane
Electrostatic interactions result in an unequal distribution of charged solutes across the membrane
resulting in excipient concentration and pH off sets
Similarly charged solutes at lower concentration on retentate side
Oppositely charged solutes at higher concentration on retentate side
Membrane
P
+
P+
P
+
P
+
P
+
P
+
Side A Side B
P + = Protein (+)
A+ = Excipient A (+)
A+
B-
A+
B-
A+
B-
B-
B-
B-
B-
B-
B-
A+
B-
A+
B-
A+
B-
A+
B-
A+
B-
A+
B-
A+
B-
A+
B-
A+
B-
High Concentration UF Formulation Challenges & Mitigation Strategies | 23 Mar 2021
14. 14
Formulation: Excipient offset considerations
Donnan Effect
65g/L Mab A, pH 5.3
10mM Histidine
MabA = +
Histidine = +
65g/L Mab A, pH 7.6
10mM Histidine
MabA = +
Histidine = Neutral
2
1
High Concentration UF Formulation Challenges & Mitigation Strategies | 23 Mar 2021
15. 15
Both strategies require
- A preliminary testing
- Formulating two different buffers:
1. Diafiltration buffer
2. Recovery buffer
Proposed Approaches:
1. Diafiltration Buffer Off-Set
2. Averaging Strategy
16. 16
Mitigating Strategies for Excipient Off-Set effect
Diafiltration (DF) Buffer Offset Strategy
5mM
Mitigated
Not Mitigated
10mM
20mM
Diafiltration Concentration
Target
High Concentration UF Formulation Challenges & Mitigation Strategies | 23 Mar 2021
17. 17
Mitigating Strategies for Excipient Off-Set effect
Diafiltration (DF) Buffer Offset Strategy
■ Adjust DF buffer composition to achieve target excipient concentrations and pH in
final product
Estimate initial off-sets via Donnan models and evaluate via experimentation.
May require several iterations to achieve final targets
■ Recovery buffer composition is standard buffer, which has been formulated at
specification
■ Advantages:
Mitigation and Recovery de-coupled.
Excipients will be on target at the end of the process
■ Disadvantages:
Increased time and resources required for iterative approach.
High Concentration UF Formulation Challenges & Mitigation Strategies | 23 Mar 2021
18. 18
Mitigating Strategies for Excipient Off-Set effect
Example of DF Butter Off-Set Formulation
■ Preliminary testing is run in order to define the level of depletion/enrichment
■ The DF buffer is formulated based on percent of enrichment or depletion
observed in the preliminary testing.
The DF buffer composition is estimated by a simple proportionality, reformulated and
checked in practice
■ TFF process rerun several times (iteration).
■ After every iteration the percent depletion is calculated and the DF buffer
reformulated to hone in on the correct formulation.
Percent Offset Depletion
Enrich buffer for DF
High Concentration UF Formulation Challenges & Mitigation Strategies | 23 Mar 2021
19. 19
Mitigating Strategies for Excipient Off-Set effect
Averaging Strategy
■ DF Buffer at target excipient concentration and pH
Estimate offset via simple models and verify via experiment
■ Use “adjusted” buffer for product recovery
pH and excipient concentrations modified in recovery buffer to achieve final pool targets
■ Advantages:
Simple and quick – Does not require complex model calcs, estimates and experimental
iteration
■ Disadvantages:
Allowable dilution limited by ratio of over-concentration to final concentration. %
Excipient enrichment can not exceed % Dilution. No issue if excipient is depleted
Recovery strategy and recovery buffer composition likely to change during scale up due
to hold up volume differences
High Concentration UF Formulation Challenges & Mitigation Strategies | 23 Mar 2021
20. 20
Mitigating Strategies for Excipient Off-Set effect
Averaging Strategy
■ Process targets:
150 L @ 180 g/L and 30 mM of [His]
Overconc. up to 225 g/L (pool) is required followed by a recovery step
• System design impact and MWV
Pool 120 L @ 225 g/L and 16 mM of [His]
Recovery Buffer volume = 30 L
■ In the Pool 0.016 moles/L*120 L = 1.92 moles
■ Target 0.030 moles/L*150 L = 4.5 moles
■ Recovery Buffer (4.5 -1.92) moles/30 L = 0.086 M/L = 86 mM/L [His]
■ Need 30 L of recovery buffer@ 86 mM [His] /L for reaching the target
final concentration
High Concentration UF Formulation Challenges & Mitigation Strategies | 23 Mar 2021
21. 21
Mitigation Strategy Comparison
Pros
Simple
Quicker development time
Iterations not required
Cons
Limited by dilution volume
Potential problem if excipient is enriched
Ties Donnan Mitigation & Recovery
Increases risk during scale up
Pros
Excipients will be on target at the end of
the TFF process
Dilution volume not an issue
Only correcting concentration not
excipient levels
Mitigation and Recovery not coupled
Reduces scale up risk
Cons
Development time is longer
More labor intensive
Several iterations may be required to
determine exact buffer formulation
DF Buffer Offset Buffer Averaging
High Concentration UF Formulation Challenges & Mitigation Strategies | 23 Mar 2021
22. 22
Summary
• Osmolality should be included in high
concentration UFDF process development.
Do not assume final product pool
osmolality = diafiltration buffer osmolality.
• Select device that balances feed channel
resistance and process flux
• Assess process for excipient offsets, and
mitigate as required.
• Consider impact of any excipient offset
phenomena on diafiltration optimization &
protein stability
23. 23
References
• H Lutz, J. Arias, Y. Zou. High Concentration Biotherapeutic Formulation and Ultrafiltration: Part 1
Pressure Limits. Biotechnol. Prog. 2017. 33 (1). 113-124
• Teeter M, Bezila D, Benner T, Alfonso P, Alred P. 2011. Predicting Diafiltration Solution Compositions
for Final Ultrafiltration/Diafiltration Steps of Monoclonal Antibodies. Biotechnology and Bioengineering
108 (6):1338-1348
• Fudu Miao, Ajoy Velayudham, Elise DiBella, Jaclin Shervin, Michael Felo, Mark Teeters, Patricia Alred.
2009. Theoretical Analysis of Excipient Concentration During the Final Ultrafiltration/Diafiltration Step
of Therapeutic Antibody. Biotechnol Prog. 25:964-972
• A Steele, J. Arias. Accounting for the Donnan Effect in Diafiltration Optimization for High-Concentration
UFDF Applications. BioProcess International. 2014, 12(1), 50-54
M.R. Stoner, N Fischer, L Nixon, S Buckel, M Benke, F Austin T.W. Randolph, B Kendrick. 2004.
Protein-Solute Interactions Affect the Outcome of Ultrafiltration/Diafiltration Operations. J Pharm
Sciences. 93:2332-2342
G Bolton, A Boesch, J Basha, D LaCasse, B Kelley, H Acharya. 2010. Effect of Protein and Solution
Properties on the Donnan Effect During the Ultrafiltration of Proteins. Biotechnol. Prog. 27:140-152
Y. Baek, D. Yang, N. Singh, A. Arunkumar, S. Ghose, AJ Li, A L Zydney, Biotechnol. Prog, 2017, Vol
33(6) : 1555-1600