Impact of imaging systems on probability of clonality (1) · 2016-09-05 · Cell Line 8 28 Cell Line 9 7 Cell Line 10 33 Cell Line 11 16 Cell Line 12 22 Cell Line 13 15 Cell Line

The impact of using an imaging system to provide the regulatory evidence that a cell line has a high probability of being clonally derived George Hutchinson VP – Asia Pacific Region

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Content

1. Review of the global adoption of an imaging system based strategy for cloning

2. Overview of regulatory requirements 3. Review of cloning methods 4. FDA requirements for imaging systems 5. Performance of imaging systems 6. Imaging systems and workflow improvements

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The view of the USFDA

• FDA 2014 “ Advances in technology (e.g. imaging) might allow for one round of cloning performed at an appropriate dilution

• Establishing Clonal Cell lines – Regulatory Perspective, Sarah Kennett PhD, Review Chief, Division of Monoclonal Antibodies, OBP/OPS/CDER/FDA, WCBP 2014

• FDA 2016 - “Considerations for commonly used cloning procedures – Single cells are plated and imaged from day 0 until the cell grows into

a colony. Supporting data should include a picture of the single cell and the entire well”

• Mitigating risk of lack of assurance of cell bank clonality on product lifecycle, Rashmi Rawat, Office of Biotechnology Products OPQ/CDER/FDA, Cell Line Development and Engineering Conference, 11-13 April 2016, Vienna, Austria拓

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Adoption of imaging systems

• Based on our market knowledge we estimate there are at least 95 biopharmaceutical companies currently using or evaluating an imaging based strategy – Of these at more than 60 are using the Cell Metric – Of those using the Cell Metric at least 25 have replaced and

existing imaging system with the Cell Metric • It is understood that very recently the FDA has approved

the first IND filing based on an imaging / one round of limiting dilution strategy

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Users of Cell Metric technology

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Users of Cell Metric Technology

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Monoclonality is a regulatory requirement

• ICH Q5D – For recombinant products, the cell substrate is the transfected cell

containing the desired sequences, which has been cloned from a single progenitor

• (US)FDA points to consider in the characterization of cell lines used to produce biologics (1993) – The MCB is defined as a collection of cells of uniform composition derived

from a single tissue or cell • EMA/CHMP Guidance on development, production, characterization

and specifications for monoclonal antibodies and related products (2008) – The cell substrate to be used for the production of the monoclonal

antibodies should be a stable and continuous monoclonal cell line that has been developed by means of recombinant DNA and/or other suitable technologies 拓

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• Since~ 2011/2012 the U.S. FDA has requested information about clonality at early IND filings:

– “Submit data to the IND that provides assurance that this method resulted in derivation of a single cell clone or provide information on how you will go about generating these data and the timeframe for submission of the information”

Regulatory and monoclonality for IND filings

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Where does the clonality of the MCB impact?

• Regulatory • Product quality • Product lifecycle • Manufacturing change • The overall Control Strategy

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Regulatory

Regulatory Considerations in Establishing Clonality for Cell lines expressing therapeutic proteins Audrey Jia, 5th Annual Cell Line Development & Engineering Asia, May 16-19 Shanghai, China

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Product quality


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Impact of clonality on product life cycle


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Impact on product quality


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Impact on Control Strategy

Mitigating risk of lack of assurance of cell bank clonality on product lifecycle Rashmi Rawat, Office of Biotechnology Products OPQ/CDER/FDA

Cell Line Development and Engineering Conference, 11-13 April 2016, Vienna, Austria

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The importance of clonality in Production

• Clonality is a regulatory requirement • Regulatory requirements for control strategy of

manufacturing changes to products derived from clonal cell banks are less stringent when compared to those for products derived from non-clonal banks

• Product quality is less variable • Easier to predict the risk associated with small

changes • Clonality impacts directly on product lifecycle拓

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Regulatory submissions


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• One cannot demonstrate clonality, rather, one can use data to show that your cell line development methods can assure that your MCB has a high probability of being clonally derived – Regulatory Considerations in Establishing Clonality for Cell

lines expressing therapeutic proteins, Audrey Jia, 5th Annual Cell Line Development & Engineering Asia, May 16-19 Shanghai, China

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Limiting dilution (LDC)

• Most commonly used cloning method – Typically use 2 rounds, seeding at 0.5 cells or less per well – Statistical analysis based upon work by Coller & Coller

(Hybridoma, 1983 2: 91-96) – Historically it has been necessary to demonstrate a probability

>96% to the USFDA • Statistical assumptions

– Cells are distributed according to a Poisson distribution – All cells have an equal chance of survival and growth

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Limiting Dilution - FDA view

Data from Kennett presentation WCBP 2014

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Limiting Dilutions - Realities

• Reality – outgrowth is significantly less than 100% – This example from BioCSL Australia

• For each of the 3 protein products, 7 sets of 4 x 96 well plates seeded with different cell lines at 0.5 cells per well

Average number of

colonies growing from

wells with single cells

Theoretical 116

Protein Product 1 18



Data source – The use of imaging to demonstrate clonality of production CHO Cell Lines – Experiences and learnings Presentation by Arna Andrews, Director, Cell Line Development, BioCSL Limited, Australia Informa Cell Line Development & Engineering Conference, April 11th 2016

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Limiting Dilutions (LDC) - Realities

• Cloning efficiency is dependent upon host cell line • Example - 4 x 96 well plates seeded at 0.5 cells per well

Protein Product

2

Colonies growing from

wells with single cells

Theoretical 116

Cell Line 8 28

Cell Line 9 7

Cell Line 10 33

Cell Line 11 16

Cell Line 12 22

Cell Line 13 15

Cell Line 14 40

Data source – The use of imaging to demonstrate clonality of production CHO Cell Lines – Experiences and learnings Presentation by Arna Andrews, Director, Cell Line Development, BioCSL Limited, Australia Informa Cell Line Development & Engineering Conference, April 11th 2016拓

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Limiting Dilution (LDC) - Realities

• Outgrowth is more likely in wells containing > 1 cell

Cell Line % outgrowth from

a well seeded

with a single cell

% outgrowth from

a well seeded

with more than

one cell

Theoretical 77% 23%

Momenta - A 46% 54%

Momenta - B 35% 65%

Momenta - C 40% 60%

BioCSL - 1 46% 54%

BioCSL - 2 54% 46%

BioCSL - 3 48% 52%

Data sources Efficient Screening Strategies to Address Monoclonality & Reduce Time Lines Chaomei He, Associate Director, Momenta Pharmaceuticals Inc. USA IBC 4th Annual Cell Line Development & Engineering Conference Asia The use of imaging to demonstrate clonality of production CHO Cell Lines – Experiences and learnings, Arna Andrews, Director, Cell Line Development, CSL Ltd. Australia Informa Cell Line Development 7 Engineering, Vienna April 2016拓

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Impact of outgrowth bias on Probability of Clonality

• Theory v Reality when seeding at 0.5 cells per well

Statistically derived

Probability of

clonality

Probability of clonality based on outgrowth summary results from Moneta and BioCSL data

0.5Momenta-

AMomenta-

BMomenta-

C bio-CSL-1 bio-CSL-2 bio-CSL-3

% of cells containing 1 cell 77% 46% 35% 40% 46% 54% 48%% of cells containing more than 1

cell 23% 54% 65% 60% 54% 46% 52%Pr of clonality after 1 round 77% 46% 35% 40% 46% 54% 48%Pr of clonality after 2 rounds 95% 71% 58% 64% 71% 79% 73%Pr of clonality after 5 rounds 100% 95% 88% 92% 95% 98% 96%

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FACS Sorting – the FDA view and new practices

“Implementation of plate imaging into our process immediately after cell sorting has yielded high resolution images of single cells. These images, together with those showing subsequent growth of a single colony are used to document that each final candidate clone is derived from a single cell progenitor”

Victor Cairns et al Sanofi (Framingham) Poster P1.69 ESACT meeting Barcelona 2015

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Regulatory requirements for FACS


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History of the ClonePix

The original ClonePixFL concept was to enable the rapid screening of 10,000 clones in one stack of 10 plates. This requires plating at 1000 clones per plate or approximately 166 clones per well. The issue of monoclonality was not an IND requirement at this time

http://www.biopharma-reporter.com/Downstream-Processing/Genetix-launches-technology-for-biopharma-development

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ClonePix and regulatory submissions


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Statistical evaluation of the ClonePix Method

• Method source - GEN tutorial – Using ClonePix FL to assess monoclonality, Nov 1, 2009

• http://www.genengnews.com/gen-articles/using-clonepix-fl-to-assess-monoclonality/3091/?kwrd=Multiplexing&page=1) • In a typical experiment, CHO cells are plated into semisolid medium to

produce 25 colony outgrowths per 35 mm diameter well (i.e., a six-well microplate well).

• At day 14, the colonies are around 0.75mm in diameter. • Using the formula (0.25 x π x (2d(c))2 x (n-1) / (0.25 x π x (2d(w))2)

• When colony number n=25, the diameter of the colony (d(c) ) = 0.75mm and the diameter of the well (d(w) ) = 35 mm, then the probability of coincidence is 4.4%

– Thus the probability of monoclonality for one round of cloning should be 95.6%.

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Statistical evaluation of the ClonePix method

• Quote from the GEN Article – “This experimental data “validates the statistical evaluation that

clonality after a single round of picking on the ClonePix FL system is >95.6% when picking larger-sized colonies (0.75mm diameter)”.

– “Using the same formula, it can be calculated that by picking at an earlier time point (when colonies are only 0.35 mm in diameter), the probability of monoclonality is increased to 99.0%. In addition, performing a second round of cloning (re-plating the picked clones and re-picking) increases the probability of monoclonality to 99.9%.”

• This data is relates to when there are 25 colonies per well

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Probability that colonies do not overlap

• “Probability of monoclonality is related to both the size and number of colonies in the well

• The formula published in GEN considers the “Probability of two colonies randomly overlapping and suggests a colony diameter between 0.35mm and 0.75mm may be optimal”

USFDA recommendation - “Data to support the clonality should include parameters used for colony selection”

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Probability colonies do not overlap

Colonies with diameter of 0.75mm Colonies with diameter of 0.35mm

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ClonePix and monoclonality

• Reality

Data source : Sarah Kennett, PH.D. Review Chief Division of Monoclonal Antibodies, presentation at WCBP, Washington DC 2014

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Probability the pin does not touch the colony

Colonies with diameter of 0.75mm Colonies with diameter of 0.35mm

Picking pin

with 2.0 mm

diameter

Picking pin

with 2.0 mm

diameter

Picking pin

with 2.0 mm

diameter

Picking pin

with 2.0 mm

diameter

Picking pin

with 2.0 mm

diameter

Picking pin

with 2.0 mm

diameter

Colonies should be at least 1.2 mm apart

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The probability to pick more than one colony

• Using the formula (0.25 x π x (d(c) + d(p))2 x (n-1) / (0.25 x π x (2d(w))2)

• d(p) = the outside diameter of the picking pin 2.0mm

This suggests that for an acceptable probability of monoclonality from ClonePix alone it is necessary to seed with a plating density of 25 cells per well or less

P(p) = Probability of only 1 colony picked

A significant contributor to the monoclonality estimate is the Probability that the pin only picks or

touches one colony

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ClonePix and monoclonality

P(c) = P(o) x P(p) x P(sc)

P(c) = Probability of Clonality

P(o) = Probability colonies do not overlap

P(p) = Probability only 1 colony picked

P(sc) = Probability subsequent sub cloning step yields a single cell拓

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ClonePix and adaptation from semi-solid media

• FDA guidance for adaptation


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ClonePix and adaptation from semi-solid media

• Most, but not all users, in the US and Europe now use their ClonePix as a screening tool to remove poor producers / growers from a population rather than use it to identify and enrich ideal clones

• Why? – They have found limited correlation between growth characteristics in

semi-solid and those in liquid media – Often the high producing colonies in semi-solid media are not the high

producers when adapted to liquid media • Why?

– Forced adaptation to culture conditions can lead to drift in genotype and phenotype in a cell

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The evolution of cell line cloning methods

• There are no “Approved” methods and you cannot “prove” monoclonality

Traditional

Statistical probability

Methods for generating the data

New

Statistical probability and photographic

evidence

Imaging systemsLimiting Dilution

ClonePix

FACS

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Imaging systems

• Current applications of imaging systems to improve cloning efficiency and probability of monoclonality – One round of limiting dilution in combination with an imaging

system has emerged as a popular alternative to the more traditional technique of two rounds of limiting dilution

– Similarly, FACS seeding in combination with an imaging system has been adopted by many large pharma in the US and Europe

– For the sub-cloning steps in the adaptation of colonies from semi-solid media to liquid media

– In combination with most other seeding methods are improved by combining them with an imaging system

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From the regulatory perspective

• From the Sarah Kennett presentation at WCBP 2014


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Will all the cells be detected?

• Will all the cells be detected? – All imaging systems have a limited depth of focus so it is important

to ensure that all cells are on the bottom of the well to avoid the appearance of false negative / ghost colonies days after seeding

• Centrifugation is therefore proposed as the most reliable way of doing this.

– It is important that the efficiency of the centrifugation process is evaluated and the Probability of a cell being on the bottom of the well determined

– It is also important to determine the Probability that the imaging system will see a cell at the edge of the well

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Will all cells be detected?

• It is important to understand how the imaging system focuses on cells because although the cells are on the bottom of the well, the bottom of each well is at a different height in the plate

• This is a focus map of a commonly used microplate, there is a variance in height of almost 350µm across the plate

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Will all cells be detected?

• It is therefore important that the imaging system has a method of tracking and adjusting the focus on a well by well basis so that every well across the plate is always guaranteed to be in focus

• In practice, users that have imagers that do not employ well to well focus tracking report the loss of up to 10-20% of wells due to the inability to locate a cell on the day of seeding – Or put another way the Probability of monoclonality is significantly

diminished if all the cells cannot be imaged

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Imaging systems and probability of clonality

Probability of monoclonality P(c)

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P(m) = P(d) x P(p) x P(int)

Where P(m) = Probability method can see 1 cell at seeding P(d) = Probability imaging system can detect 1 cell P(p)= Probability cell is in a position that makes it detectable P(int) = Probability the image can be correctly interpreted by the user

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The probability that imaging system can detect 1 cell is related to the image quality

Evenness of Illumination

Camera resolution (µm per pixel)

Data Compression

Depth of focus

Image Stitching

Focus

Contrast Monitor Resolution

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• Probability imaging system can detect 1 cell is related to image quality which is defined by: – Focus – Evenness of illumination – Contrast / dynamic range – Accuracy of positional relationship between well and

lens (image stitching) – Depth of focus / Numerical aperture – Data Compression – Resolution of monitor – Resolution of camera (optimum number of µm per

pixel) • 2µm per pixel is optimal for CHO cells • Note you can have too much resolution as well as not

enough resolution

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• Probability cell is detectable is defined by: – The cell being on the bottom of the well – Adapting to the changes in the position of the

well bottom across a microplate

• Probability the image is correctly interpreted by the user – Procedure requires more than 1 verifier – Ability to accurately locate any image

associated with a well at any time • Bar codes for correct plate id and orientation

• Integrated reporting to eliminate cut and paste errors拓澳生物


Performance of imaging systems

• At the present time there is limited published data on the Probability of Monoclonality using an imaging system

• The data that is available suggests that if the correct methodology is applied then the Probability of Monoclonality is >99%

• The USFDA have in the past few weeks accepted an IND filing where the monoclonality probability has been determined using an imaging system

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Clone Screening – Data Collection

• Image microplates repeatedly over time • Confirm single cell arrival in the well • Confirm subsequent growth and division into a colony拓

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Clone Selection – Data Review

• Track backwards and review wells • Select those which are single cell origin拓

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Clone Selection – Data Review

• Highest quality image of single cell • Combination of 3 factors: Focus, Resolution, Contrast拓

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Clone Proof – Report Generation

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Image of the entire well needed

• Software demonstration

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Imaging system deliverables

• FDA requirements – Cells at edges of wells – Differentiate between 1 and 2 cells – Single colony not sufficient (single cell image needed) – Image of the entire well needed

• Additional information provided by imaging – What is in the plate before seeding – Images growth from single cell, to two cells, to small colony

onwards – Hard copy of images that are time stamped and cannot be edited – Image can be reviewed many people, at time of project, months

after project and years after project 拓澳生物



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What happens if the cells move during the study?

1. The regulatory requirement is to show an image of a single cell, a whole well image and show that the system can differentiate between one and two cells

2. As part of the method validation it is necessary to determine the probability of there being only one cell in the well at time of seeding • This usually involves a statistical analysis of the number of ghost

colonies that appear • If on subsequent time points the cells move then this does

not affect the probability of monoclonality • The practical reality is that some cells do move and colonies

disperse in wells over time even if they have been derived from a single cell

• A well that contains a dispersed colony or more than one colony may still have been seeded with a single cell

• Viewing additional time points is a useful activity to help locate the position of a single cell that on day 0 and monitor colony growth. 拓

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Formation of a single

colony (day 5-7)

Image of a single cell

on day 0

Image after doubling

(typically day 1)

Documentation to support regulatory filing

from only one round of sub-cloning,

irrespective of the seeding method

First round of Limiting dilution

FACS sorting

Post adaptation from semi solid

media

Day 7 - 14 Select clones of

interest based on colony

growth and track back to look

for single cells

Day 0 - Seed cells

Summary of the cloning process when using an imaging system

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Comparison of sub-cloning methods

Method Day 0 to 14 Day 15 to 28 Day 29 to 42Probability of

clonality

Limiting Dilution Round 1 Round 2 Statistical

FACS Seeding Statistical

Clonepix Round 1 Round 2

media

adaptation /

sub cloning

Statistical

Limiting Dilution &

ImagerRound 1 Evidence based,

typically >99%

FACS & Imager Seeding Evidence based,

typically >99%

ClonePix & Imager Round 1

media

adaptation /

sub cloning

Evidence based,

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Imagers open new possibilities

• The data here, courtesy of Arna Andrews of BioCSL, shows it is now possible to seed at densities of 1 cell / well and greater and improve cloning efficiency

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Setting new expectations

• If performed appropriately, a single round of cloning associated with imaging outperforms two rounds of LDC assessed via Coller & Coller statistics

Data source – The use of imaging to demonstrate clonality of production CHO Cell Lines – Experiences and learnings Presentation by Arna Andrews, Director, Cell Line Development, BioCSL Limited, Australia Informa Cell Line Development & Engineering Conference, April 11th 2016

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Range of ProductsCell Metric Cell Metric CLD

Throughput Single plate Incubated 10 plate delivery system

Speed – Verify Clonality Mode (highest contrast)

4 – 5 min/plate Same as Cell Metric

Speed – Clone Growth Mode

3 - 4 min/plate Same as Cell Metric

Image quality Dynamic autofocus High contrast imaging Even illumination of entire well Optimal resolution

Same as Cell Metric

Metric Verify clonality Confluence (growth rates) Colony Counting option

Verify clonality Confluence (growth rates) Colony Counting option

GMP status IQ/OQ Documentation Package IQ/OQ Documentation Package

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In conclusion

• From a regulatory perspective clonality is important in all stages of the process – Recommendation is that clonality to be established early in the product

development – USFDA now regard using an image as a “commonly used cloning method”

• Statistical methods may require re-evaluation now that it is possible to determine with a high probability if there is none, one or more cells in a well

• Imaging systems are compatible and improve most seeding methods in terms of workflow efficiency and quality of results

• Imaging systems deliver evidence which can be referred to at any time of the product lifecycle

• New, more efficient seeding methods may be possible拓澳生物


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Documents

Impact of imaging systems on probability of clonality (1) · 2016-09-05 · Cell Line 8 28 Cell Line 9 7 Cell Line 10 33 Cell Line 11 16 Cell Line 12 22 Cell Line 13 15 Cell Line