Introduction to filter sizing

Vmax and Pmax method Presentation Overview

 How a Filter Works

 Key Membrane and Depth Filter Characteristics

 Filter Fouling Mechanisms: An introduction to Filter Sizing and Scaling Models

 Gradual Pore Plugging Model and Vmax method

 Pmax/Tmax Method

 Safety Factor consideration

15/5/2017 How a Filter Works Microporous Membranes

Virus Membranes

Ultrafiltration Membranes

Reverse Osmosis Membranes 15/5/2017 Retention Mechanisms

 Describe how filters capture (retain) particles  Mechanisms can be affected by: • Fluid characteristics • Operating conditions • Particle type • Filter type  Retention mechanisms form the foundation of filter fouling models

15/5/2017 Particle Retention Mechanisms

. Size Exclusion - Plugging • Sieving (surface) • Entrapment (depth) • Size-dependent

. Adsorption • Attraction forces between particles and filter material • Molecular and/or electrical • Not size-dependent

. Depends on • Particle type • Solution properties • Filter material and structure Key Membrane and Depth Filter Characteristics What do Membrane Filters look like?

 Mainly made by casting membrane  Can be either hydrophilic or hydrophobic  Rated on the size of the smallest particle it retains  Very thin (100 - 260 um)  Adsorption depends on materials • Not the primary retention mechanism  Examples • Cellulose ester • Regenerated cellulose • Nylon • Polysulfones • PVDF

15/5/2017 Key Membrane Filter Characteristics

 Strong, Rigid NOT brittle

 Tortuous pathway

 Very high internal area

 65-75% porosity

 Size exclusion - particle retention does not change with flow or pressure

 Sterilizing filters must have > 99.99999% removal and sterile filtrate

 Integrity testable (diffusion &/or bubble point)

15/5/2017 What do Surface (Pre-) Filters look like?

 Fibers locked together by heat or membrane coating

 Given a nominal rating or rated by the filter it protects

 Thin (1 mm or less) & Slightly Adsorptive

 Give a percentage (90 - 99.9%) particle reduction

 Examples • Cellulose ester coated cellulose or polyester web • Heat-treated polyproplylene filters

15/5/2017 What do Depth Filters look like?

 Fibrous (can shed fibers)  Difficult to give an accurate pore size rating  Thick (3 - 30 mm) & often adsorptive  Give a percentage (i.e. 30 - 70%) particle reduction  Have the greatest capacity  Examples • Microfiberglass • String-wound filters • Sheet / pad filters

15/5/2017 Depth filter composition

. Cellulose fibers base matrix • Highly refined . DE (Diatomaceous Earth) Diatomaceous Earth • Refined grade • Large surface area • Entrapment sites . Resin binder • Positive charge & hydrophobicity for adsorption

Filter Matrix Cross-Section @ 3656 X

15/5/2017 Filter Fouling Mechanism:

An introduction to filter sizing Types of Particles in Biological Fluids

 Non-deformable types • Resin beads or fines • Drug crystals • Carbon fines • Diatomaceous Earth (D.E.) • Form porous permeable cakes.

 Deformable types  Proteins

 Lipids

 Sugar/protein complexes

 Can move through the filter, break-up and compress into impermeable cakes.

15/5/2017 Cake Formation

 Happens with hard particles

 Particles build up on the surface of the filter

 If particles are rigid, resistance increases linear with cake thickness

15/5/2017 Complete Pore Blocking

 Happens with deformable particles

 Pressure forces particles to completely block the "pore"

 Common when there is poor or no prefiltration OR when soft particles slightly larger than the filter rated pore size

15/5/2017 Gradual Pore Plugging

 Happens with hard or deformable particles

 Particles build up on the "pore" throat or opening

 Filter slowly blocks

 Most common with biological fluids

15/5/2017 Impact on Filter Behavior

 Gradual blockage most common

 "Everything was going alright, then all of a sudden the filter plugged"

Constant flow filtration – ∆p increases as filter fouls Gradual and complete blocking do not have a linear relationship between ΔP and capacity

15/5/2017 Filter Performance Characterization

.Filter performance is defined by two key attributes

.Capacity • Volume that can be process per filter area (L/m2) • How much?  Flowrate • Volume processed per time per area (L/m2/hr = LMH) • How fast? .Performance depends on: • Filter selection- the correct filter for the application • Process parameters • Optimizing pressure, flowrate, time, area

15/5/2017 Small-Scale Test Methodologies

Constant Pressure (Vmax) Constant Flow Rate  Fluid is held at constant (Pmax/Tmax) pressure and forced through  Fluid is pumped at a constant filter media flow rate through the filter  Filter plugging is observed by media the decrease in flow rate over  Filter plugging is observed by time an increase in differential  Classically, based on pressure over time gradual pore plugging OR model  Filter plugging is observed by an increase in filtrate turbidity over time  Based on a small-scale process simulation with

15/5/2017 empirical data fitting Choosing a Filter Sizing Technique: Fouling Mechanism Basis

Constant Sizing Method Name: Pressure Vmax Volume Endpoint Vmax

Constant Tmax Pmax Pressure Endpoint Pmax Flow

∆P does ∆P increases during Turbidity Endpoint Tmax Mode Testing of not change filtration

Size Exclusion Mechanisms Choosing a Filter Sizing Technique: Filter Type Basis

Tmax

Pmax Pmax (Applicable, (Application Focus) but less common)

Vmax

Depth Membrane and Non-woven Sterilizing-grade Filters Prefilters Membrane Filters

15/5/2017 Gradual Pore Plugging and Vmax Method Available Test Methodologies for Sizing Filters

Constant Pressure (Vmax) Constant Flow Rate (Pmax)  Measures decrease in flow as a  Measures increase in pressure and function of throughput decrease in filtrate quality as a function of throughput  Endpoint is determined by flow rate or volume  Endpoint is determined by pressure limit or desired filtrate quality

pressure turbidity flow rate

throughput throughput

15/5/2017 Filter Plugging Models

.Mechanism of filter plugging:

• d2t/dV2 = k(dt/dV)n where: t = filtration time V= cumulative volume at time t k = constant whose dimensions are dependent on n n = 1.5 for gradual plugging

• H.P. Grace, "Structure and Performance of Filter Media," AICHE Journal 2(3), 307-336 (1956) .In practical terms:

• t/v = t/Vmax + 1/Qi where:

Vmax = maximum volume that can be filtered at time infinity

Qi = instantaneous initial flow

15/5/2017 The Vmax (Constant Pressure) Test

• Accelerated screening technique to estimate scaled-up filter size requirements • Helps to optimize filtration train rapidly

• Estimates the maximum fluid volume filterable through a filter – Predicts Capacity, Vmax [=] L/m2 (@ t=∞) – Predicts Flux Decay Profile , Q [=] L/min • Vmax Characteristics – Based on the gradual pore plugging model • Vmax Implementation – Plot t/V versus t at constant ∆P – Vmax = 1/Slope, Qi = 1/Intercept

15/5/2017 Vmax: Result Analysis

. Typical Curve

• Highly linear region r2 > 0.99 2 − r > 0.99 1/Q i 1/Vmax . What happens when r2 < 0.99? t/V • Prediction of Capacity (Vmax) based on 10 min test becomes less reliable • Remove earlier points to see if fit is t improved, − Need at least 6 points in the straight line for reliable correlation r2 < 0.99 . Run test to 80% plugging (flow t/V decay) 1/Vmax t Vmax: Approaches to Filter Sizing

.Three process scenarios or cases are usually relevant: • Case 1: Batch Volume of fluid to be filtered is given • Case 2: Batch Volume of fluid to be filtered at a maximum allowable process time is given • Case 3: Batch Volume of fluid to be filtered with a specified minimum allowable flow rate is given

.Largest surface area that fulfills all process requirements is selected, Amin

15/5/2017 Vmax: Sizing Equations

Case 1. Only VB (Batch Volume is given; No batch time, minimum flow)

VB Amin = Vmax • Eq. gives the minimum area required (no safety factor is included)

• Ensure that Amin leads to respectable batch times

Case 2. VB (Batch Volume) and tB (Batch time) are given VB VB Amin = + Vmax Qi ×tB

Case 3. VB (Batch Volume), tB (Batch time) & Qmin (minimum flow rate) are given Q V 1− min = B Qi × Amin Vmax × Amin

• Using an Iterative Method, Solve Eq. For ‘Amin’ •‘Case 2’ can give a reasonable initial guess 15/5/2017 Vmax: Advantages/Benefits

.Simple, rapid & easy to use .Experimental basis for filter train selection • Establishes optimized filtration train and preliminary information for scale-up, confirmatory pilot scale trials .Results have simple interpretations: • Vmax - maximum ‘filterable’ fluid volume before plugging, L/m2 • Qi - initial filtrate flowrate; L/min/m2 .Requires only limited fluid volume to perform the test. • < 1 liter

15/5/2017 Vmax: Limitations

.It does not tell you which filter to test • Experience & historical records are useful .Does not tell you anything about filtrate quality • Indirectly Vmax, with a tighter filter, on the filtrate is a measure of filtrate quality .Does not simulate the entire process • Need for intermediate pilot trials .Only applies to gradual pore plugging model

15/5/2017 Pmax/Tmax method Large scale  Small scale

Golden rule:

“ During PD, in small scale experiments, mimic large scale operation as close as possible”

. Process parameters . Fluid characteristics

15/5/2017 Challenges to Clarification Process Optimization

Three process challenges when developing a clarification scheme: 1. Understanding fluid complexity and characteristics 2. Understanding how to select optimal separation technology 3. Integrating clarification technologies to achieve the optimal clarification scheme

15/5/2017 First Process Challenge: Understanding Fluid Complexity

Biological Fluid Constituents

– Solids (> 1 µm) – Soluble entities • Easily removed by depth entrapment, • Protein cake build-up or centrifugation – Cell culture fluids – Cells and organisms (0.2 - 50 µm) – Lysates • Mammalian cells – Plasma fractions – Delicate, can lyse under stress and release plugging materials • Salts • Others – Buffers – Bacteria, yeast, insect, plant • Preservatives – Ophthalmics – Colloids (0.01 - 1.0 µm) • Deformable and “sticky” • Anti-foams • Usually negatively charged – Cell culture fluid • Plug downstream steps • Plant hydrolysate& serum – Cell culture media

15/5/2017 Second Process Challenge: Optimal Technology Selection

What Technologies Are Available?

Separation Application Benefits Limitations Technology Scope

Simple scale up and No filter re-use, High Clarification, implementation, Multiple media NFF expendables, Limited by solid Prefiltration options (Surface, depth, load charged) Clarification, Efficient and robust process, High capital cost, Difficult to TFF Concentration, Can handle high solid loads, operate/validate Cell recovery Re-usable filters Cheap operation, No Mechanical Clarification High Capital cost, Source of expendables, Robust, Re- Separators Only yield loss, Difficult scaleablility usable, Easy to clean

15/5/2017 Third Process Challenge: Optimizing Technology Integration

Cell Density

High TFF or centrifuge + 1-stage charged TFF TFF or centrifuge depth filter + 2-stage charged depth filter Med Depth filter 1 or 2-stage charged Low TFF or centrifuge depth filter + 1-stage charged Surface filter depth filter Cell Viability

Low Med High

Integrating Multiple Technologies Will Achieve The Optimal Clarification Scheme 15/5/2017 Filter Selection Rules of Thumb

Fluid Fluid Components/ Recommended Filters Turbidity Characteristics

< 20 NTU Colloids, small Protected sterile filter (0.45/0.22 µm particulates Durapore, Express SHC)

20-100 NTU Colloids, small Membrane, cartridge-style pre-filter particulates (Milligard, PolySep II)

100-300 NTU Colloids, cell debris, Smaller pore depth filter particulates (X0HC, A1HC, B1HC) (2nd clarification) > 300 NTU Whole cell, hard Larger pore depth filters particles, cell debris (D0HC, C0HC, DE50) (1st clarification)

15/5/2017 Capacity

.Goal: • Maximize the amount of fluid that can be processed through a filter.

.The question is: "At what point does the filter resistance (pressure) or filtrate quality negatively impact the process?" • excessive pressure • excessive turbidity breakthrough

.Capacity The volume filtered up to the point when the maximum pressure or turbidity is achieved • defined in volume/area (L/m2)

15/5/2017 The Pmax/Tmax (Constant Flow) Test

.Using a peristaltic (or other positive displacement) pump, a constant flowrate is maintained

.Process simulation technique (scale-down)

.Estimates the maximum fluid volume filterable through a filter − Pressure Limited Capacity (Pmax) − Filtrate Quality Capacity (Tmax)

.Calculate resistance as a function of volumetric throughput

.Sizing is based on an empirical model

15/5/2017 Methodology: Pmax constant flow, P limitation

.Constant flow filtration – pressure increases as pores are blocked .Flow rate through membrane will depend on installed area

Maximal pressure

Pressure (psi)

Time(h) ~Volume (L)

Area of filter 1 < Area of filter 2

15/5/2017 Methodology : Pmax

. Maximum pressure P and process time & volume defined as end point. Pressure (psi) .Define resistance (psi/LMH) as pressure per flow rate (J) per area Time(h) ~Volume (L)

.Define throughput as volume per area (L/m2)

Resistance Pmax (L/m2) (psi/(L/m2/h))

Throughput (L/m2)

15/5/2017 Analyzing Test Results

.Fit the data to a 2nd or 3rd order polynomial − Choosing the “best fit” comes with experience—it is a judgment call − In general: − Polynomial must have the correct concavity when projected forward − Polynomial must accurately model the “pressure rise” region

.Use the Pmax sizing algorithm for a

known batch volume (VB), batch time (tB)

15/5/2017 Applying the Pmax Sizing Algorithm

Pmax Sizing Algorithm: • Example Sizing (VB=1000L tB = 4 hr): Fig. 1 - Resistance vs. Normalized Volume 1. Guess an area & select ∆Plimit Resistance for process endpoint Permeate NTU 0.70 1.2 0.60 2. Calculate Flux, Javg = VB/AtB 1 3 2 0.50 y = 2.20E-08x - 6.13E-06x + 7.44E-04x - 2.53E-02 0.8 and Capacity = VB/A 0.40

0.30 0.6 3. Calculate Resistance, Rcalc. = 0.20

0.4 Permeate NTU

∆ Resistance (psi/LMH) 0.10 P/Javg. 0.2 0.00 0 50 100 150 200 250 300 350 400 450 -0.10 0 4. Determine Actual Resistance Capacity (L/m²) from the graph or Polynomial 2 1. Guess A=3.0 m , Plimit = 15 psid fit, Ractual 2 2. Javg = 83 LMH, V/A = 333 L/m 5. Check to see if Rcalc = Ractual 3. Rcalc = 15/83 = 0.18 psid/LMH • If yes, selected A is correct 4. Ractual = 0.36 psid/LMH • If Rcalc < Ractual, increase 5. Rcalc < Ractual ∴ increase A & reiterate Area (A) & iterate until Rcalc = Ractual 2 • Amin = 3.5 m 15/5/2017 Pmax/Tmax: Advantages/Benefits

.Applicability is independent of the plugging model − Uses an empirical data analysis method to analyze constant flow data − not based on any mathematical model

.Results have simple interpretations and provide basis for implementation (process simulation): − Pmax − maximum ‘filterable’ fluid volume before pressure limit, L/m2 − Tmax − maximum ‘filterable’ fluid before filtrate quality limit, L/m2

15/5/2017 How Accurate is the Pmax Sizing Method?

. Pmax can be very accurate when process parameters between large and small-scale are carefully controlled

. Example at right resistance (LMH/psi) shows a 130X scale- up/scale-down filter loading (l/m2)

Millistak Mini (2X flux) Millistak Mini (1X flux) Millistak Pod (1X flux) sizer prediction Pmax/Tmax: Limitations

• Uses an empirical data analysis method to analyze constant flow data—not based on any physical model

• Requires longer test times – Close to process times – No extrapolations to higher loadings

• Checks need to be put in place to guarantee adequate fit of resistance curve

15/5/2017 Safety Factors Considerations Safety Factors: Introduction

General rule is 1.5X but… It depends!  Amount and quality of data  Expected variability of feed  Expected variability of filter  Existing equipment  Scaling factor

15/5/2017 Safety factors

.“Variability is typically normal”

.To allow for variability in your process, a safety factor is applied.

.Depending on your unit operation and information on typical variability, this safety factor should be smaller or larger. - i.e. control over cell culture consistency, centrifuge operation can reduce required safety factor and make secondary clarification very economical, lack of control might lead to large installations.

.Risk/cost based approach

15/5/2017 Safety Factors: Using a cost benefit analysis

. Analysis based on a sample

of sterile filters $10,000 . Lower area yields lower $9,000 $8,000 fail batch overall cost but increases $7,000 yield loss risk of a failed batch $6,000 labor $5,000 total buffer

$/batch $4,000 . Higher membrane area capital $3,000 increases overall cost but consumable $2,000 risk of lost batch is $1,000 decreased $- 1 2 3 4 5 6 7 8 9 12 15 18 21 38

4" Opti MPAK20 MPAK40 MPAK60 MPAK100 MPAK200 # 10" elements

• Existence of a minimum value for a failed batch vs. overall cost is the base case for determining a safety factor Safety factor: Choosing a robust safety factor

1000.00 Safety 1.1 .Each unit operation has its Factor own range of 1.2 1.4 100.00 • Cost ratios Sterile Bulk Clarification 1.6 1.8 or media or Virus • Variability 2 10.00 2.2 .Similarly, each unit 2.4 Cost Ratio operation has its own range Sterile 2.6 2.8 of safety factors 1.00 Buffer 3 .“Standard” safety factors 3.2 3.4 may be insufficient 0.10 0% 10% 20% 30% 40% 50% 60% Coefficient of Variation of Area

Cost of batch Safety Application failure Area Variable cost Cost ratio COV Factor Final Bulk sterilization $500-1500K 1-7 sqm $0.4-0.6 K/sqm 400-800 10-30% 1.4-2.0 Buffer sterilization $5-50K 1-7 sqm $0.4-0.6 K/sqm 5-25 5-10% 1.1-1.3 Growth media sterilization $50-500K 1-7 sqm $0.4-0.6 K/sqm 50-250 10-30% 1.3-2.0 Clarification $100-1000K 1-30 sqm $0.3-0.5 K/sqm 50-250 30-60% 1.8-2.8 Virus filtration $500-1500K 1-7 sqm $2.8-7.5 K/sqm 30-250 40-60% 2.0-3.0

15/5/2017 Safety Factors for Depth Filtration

Variable Failure Safety Application $/g $/g CR COV Factor Sterile Bulk 0.03-0.10 100-300 1000- 15-20% 1.6-1.9 Buffer 0.2-0.4 1-2 2-10 15-20% 1.3-1.5 Media 0.6-2.1 10-100 15-50 10-30% 1.3-1.9 Series 0.1-0.3 100-300 3000-7500 15-20% 1.6-1.9 Clarification 1.4-5.3 20-200 5-150 25-40% 1.5-2.3 Retrovirus 0.4-0.7 100-300 150-750 15-25% 1.5-1.9 Parvovirus 3.2-32.0 100-300 3-90 25-35% 1.4-2.1 UF 0.1-0.3 100-300 300-3000 5-25% 1.2-2.1

• Depth filtration has a relatively high cost ratio due to a relatively high variable cost ($/g) • The cost-benefit analysis suggests that safety factors of 1.5-2.3 are justified • Historically, safety factors as high as 3.0 have been employed in depth filtration operations (depends on control over feed variability)

15/5/2017 Wrap-Up

.Good filter sizing starts with well-designed small-scale trials − Multiple experiments − The right test methodology − Proper understanding of sizing techniques .Intermediate (pilot-scale) trials will ensure smooth scale-up .Implementing the “right” filter involves more than capacity; other considerations include: − The right safety factor − Process limitations − Hardware constraints − SIP requirements − Robust IT operations

15/5/2017