The Future of Cell-Line Development

0:52 

Hello, everyone. 

 
0:54 
Welcome to this monthly Science Exchange series. 

 
0:59 
It is my great pleasure to welcome you too to today's session on the future of the cell line development. 

 
1:07 
My name is Chris Anthe, I'm a scientist too and the vectored process development team here at Orchard and I'm honoured to be the leader of the session today. 

 
1:17 
And we will be covering the a very exciting topic on the stable cell lines and achievements, new technologies, applications in the field and how the future might look like. 

 
1:28 
And then from my side, yeah, very also special. 

 
1:32 
Welcome to the panellists today, Michael and Martin and Selassie. 

 
1:40 
Yeah, we appreciate being here. 

 
1:43 
And so, yeah, to like kick off the session, I will start with the presentation and then we can move on to the panel discussion. 

 
1:51 
So I will start by sharing my screen. 

 
2:07 
Great. 

 
2:07 
So today hopefully I will give you an overview of the cell and development technology and how the future might look like. 

 
2:20 
This is the agenda of my presentation. 

 
2:22 
I will start with a brief introduction on the stable cell and technology and then workflows that are essential to develop a stable cell lines, key technologies that we have at the moment, the introduction of automation into the cell and development platforms and then some final remarks. 

 
2:43 
So as an introduction, I mean, I'm sure you're all aware of this, but yeah, generation of the stable cell line refers to the process of a developing homogeneous population of cells that demonstrate expression of the transfected gene insert and the transfected gene integrates into the genome of the whole cell and they as a result consequently expressing the transfected genetic material. 

 
3:10 
And this is the opposite of the transient transfected cells that expressed in transfected DNA for a short time. 

 
3:17 
The stable lines are widely used in several important applications, and some of the common applications would be recombinant protein production for cytokines, enzymes, antigens, antibody production for monoclonal antibodies, viral vector production for example, antiviral vector production, cell and engineering for research and screening for gene functional studies and drug screening, and finally in vaccines and gene therapy for AAV production and vaccine. 

 
3:58 
And there is always a debate between stable cell alliance and transient transaction. 

 
4:05 
I mean there are pros and cons in for example, in the transient transaction, this is allows expression of a viral cytotoxic proteins and it is much shorter comparison to stable lines. 

 
4:25 
But there are lots of cons for example, but vast variability. 

 
4:30 
It is labour intensive and low adaptability in the in larger scale. 

 
4:35 
And there is always the cost and the stable supply of the GMP plasmid and reagents. 

 
4:41 
And there are higher impurities in the final product where for the stable cell lines there is no need for GMP supply of the transmission reagents and plastic stocks all the time there is buts to buts consistency. 

 
4:53 
The platform is offers scalability and process intensification and they can be maintained for lower cost and effort. 

 
5:02 
But of course to develop a stable line is time consuming. 

 
5:09 
I'm going to briefly describe a typical workflow for a cell line development to produce a producer a stable cell line. 

 
5:19 
And this will start with preparatory activities such as constructing the genome and functionality testing and sequence the plasmid. 

 
5:31 
And then it would be the stable transfection to generate a stable pool and the screening of the stable pools. 

 
5:40 
And this will follow the actually development of the suspension producer cell lines, which include the single cell isolation and the screening of all the clones that are generated from the single cell isolation through different stages from 9:00 to 6:00, well plates up to a sake flasks and then through this different stages of screening and reducing the number of clones in every round, we will end up with the top producers. 

 
6:18 
And this will go into stability for around three months in the presence and absence of antibiotics and then all run all the analytical assays, for example, copy number, title, stability, viability, cell growth and expression with or without selection and further characterization to determine the top producer. 

 
6:43 
So this would be a general overview of an A vector production, but there is also a similar workflow when it comes to producing recombinant proteins, which again starts with the transfection and with the recombinant plasmids encountering the protein of interest. 

 
7:07 
And then we are moving into the selection of the transfected cells, clonal screening and then cell line characterisation and expansion. 

 
7:17 
So as you can see, the main four key steps when developing a stable cell line are the same whether you are developing for a vector production or proteins or antibodies. 

 
7:33 
Of course, there are differences in when you characterise and in the selection assays, but the main steps are similar and there are key technologies that are out there, new tools and methods that have been developed to assist in the in this process. 

 
7:55 
It is essential to optimise your platform and optimization, and further work is required to lock each step of the workflow established. 

 
8:08 
Best practises for generating and maintaining stable cell lines include the selection of the host cell line, the stable line technologies primary utilising mammalian cell lines. 

 
8:22 
But the importance of early decision of the nature of the culture and to an extent of your whole platform to be based either in adherent or suspension conditions will prevent the impact of suspension adaptation serum free cultures later on that can potentially change the ranking of your high producer clones and maybe the production. 

 
8:49 
So it is always advisable to know your top producers from the beginning. 

 
8:54 
And next would be plasmid preparation with codon optimization and sequencing. 

 
8:59 
Another important step is to optimise the transfection methods to maximise transfection efficiency while minimising the cell toxicity. 

 
9:09 
And this may they may involve testing different parameters, transfection reagents and optimising the transfection conditions such as like cell density or DNA concentration and transfection reagent ratios. 

 
9:29 
The next big step is monoclonality and monoclonality assurance. 

 
9:35 
So there are different methods to achieve that and different high throughput images available. 

 
9:42 
And another bottleneck on this step is the survival of single cells and this can be achieved through supplementation and recovery media optimization. 

 
9:54 
Next would be and the analysis of the expression and then screening step where you have to decide on the screening throughput and the number of clones to screen per campaign. 

 
10:07 
And finally all the assays for the thorough characterization and validation of the stable cell lines. 

 
10:16 
So what I've described was the key main steps in the workflow, but there are also additional variables to consider when you establish a workflow. 

 
10:28 
For example, protein localization, if this will be cytoplasmic and membrane or secreted. 

 
10:35 
As I mentioned, wholesale properties in adherence, suspension, culture and growth conditions, all the environmental conditions, temperature, gas concentrations, media components. 

 
10:49 
If you want to have random or targeted integration, the vectors and promoters that you will have to use all the culture vessels and the stages, the culture stage of your clone. 

 
11:04 
And then of course the selection and selection markers and reporters. 

 
11:11 
Starting about the consideration of the hostel line selection, there should be a clear traceability of self-source. 

 
11:21 
A testing and characterization will include suitable for GMP production of the therapeutic protein and it can be the cell line should be easily adapted to serum free and suspension growth conditions with high growth rate, a well termed high secretory capacity, stable product quality and productivity over time, and also to be able to give you short timelines from gene transfection to production cell line, they're commonly used wholesale types are toe cells and hex cells, so the toe cells are mostly used for production of the therapeutic proteins. 

 
12:08 
They are epithelium cell line derived from the ovary of the Chinese hamster. 

 
12:15 
They are widely used in studies of genetics, toxicity, screening, and, as I said, expressing recombinant proteins, and are mostly used for industrial production of proteins and antibodies. 

 
12:34 
On the other hand, the hex cells is the gold standard for vector production and the an important variant of this cell line is the 293T cell line where the SB-40 likes. 

 
12:48 
The antigen allows the amplification of transfected plasmid and extended temporal expression of desired gene products. 

 
12:59 
And when it comes to transient integration technologies, this is a big discussion. 

 
13:05 
There are many technologies available nowadays when someone can start from the one way stable transfection. 

 
13:15 
In that case, for example when it comes to lentiviral vector production to transfect the transgene, VSV-G, Gag-Pol and rev plasmid all in once to create a stable cell line. 

 
13:28 
But there is a common practise to create a packaging cell line first by stable transfection of the VSV-G, the Gag-Pol and the Rev plasmid into the host cell line and use these as a starting host cell line to create your producer cell line by stable integration of your transient. 

 
13:50 
There are of course other technologies, for example the back technology which is patterned in from GSK where all the four viral components are cloned into a bacterial artificial chromosome and this is stably transfecting into the host cell lines. 

 
14:06 
But there is also the transposase mediated integration which is a platform that I know Lonzo is currently utilising where there is a circular DNA vector which contain your gene of interest and that is surrounded by inverted terminal repeat sequences. 

 
14:28 
And this is the transpose zone and this is introduced into the host cell along with the transposase enzyme and these the transposase recognises the ITRs at the it's end of the genome interest and these where it cleaves the DNA and it pastes into specific sites in the host genome. 

 
14:57 
And there are also inducible systems and gene expression stable lines that are used for recombinant protein expression in cell cells and vector production with cytotoxic envelopes in hex cells. 

 
15:13 
Then that is achieved through the induction of the genes of interest by tetracycline or it's analogues, for example, toxic cyclin and they're usually based on the Tet-regulated in expression and they are usually Ted on systems where production is occurring by the addition of toxic cycling to the culture media. 

 
15:36 
So how that works is that the gene of interest is under the control of the engineered tetracycline operator. 

 
15:46 
That ETO just going to use my laser so you can follow me how I describe it so that you have the tetO containing promoter and the test response element. 

 
16:00 
The Tre as we say is repeats of this operator and is recognised by the tetracycline repressor. 

 
16:11 
So this binds to the Tre and blocks the transcription of the gene of interest. 

 
16:17 
But when you add the doxycycline, which is the synthetic analogue of the Tetra tetracycline and that leads to binding in the tetR and then and the release of the tetO and then that's these results into the repression of the promoter and the transcription of the gene of interest. 

 
16:44 
And when it comes to the single cell cloning procedures and the assurance of monoclonality, we know that this is a regulatory requirement. 

 
16:54 
And it is clearly stated in the ICH SQ5D section of the FDH 21 CFR where it states that recombinant products, the cell substrate is the transfected cell containing the desired sequences which has been cloned from a single progenitor. 

 
17:16 
Traditional methods to generate the monoclonal cell line included serial dilutions, limiting dilution cloning and single cell sorting, where the common practise used to be two rounds of limiting dilution or one round of limiting dilution cloning with imaging supporting data of the whole well. 

 
17:38 
And again, it's not the same to observe 1A final colony as imaging a single cell at day one, because this can could have been two colonies from two single cells that merged and formed the final colony. 

 
17:54 
So for this purpose we would need a high throughput imager for the proof of monoclonality. 

 
18:01 
But most of the workflows and platforms nowadays have introduced the automated single cell isolation systems and technologies to reassure their monoclonality in this step. 

 
18:21 
And then another huge bottleneck I would say in the cell and development is the data management. 

 
18:28 
So even most innovative organisations are still facing significant that the challenges in cell and development and modern cell and development is becoming increasingly sophisticated and data silos between cell and development process steps, operators and labs can lead to rework bottlenecks and issues with data integrity and compliance. 

 
18:56 
So, advanced bioinformatic tools and knowledge management systems are becoming increasingly important. 

 
19:04 
In this context, effective data management allows us to automate screening process, track the full lineage history during cell banking and transfer full sample context from other teams. 

 
19:18 
So also detailed documentation, record keeping of the entire process including protocols, methods, assays, procedures and characterization data are also critical. 

 
19:32 
And this ensures reproducibility, allows for troubleshooting if any issues arise and also facilitates knowledge sharing with regulatory authorities. 

 
19:43 
So transitioning from handwritten notebooks to electronic lab notebooks in an important improvement to the sale and development data management as an electronic lab notebook will give you electronic access to all experiments and there are notebooks which give you a specific ID for its individual experiment. 

 
20:12 
You can have templates for its workflow. 

 
20:16 
Storage and unique names for it's saline and data analysis templates and reliable data storage for traceability. 

 
20:26 
And in general that a data management platform will allow you to automatically link data from different platforms and store them into one place to manage real time inventory, barcode tracking between different plates and wells when you are screening your clones or during the single cell isolation process. 

 
20:54 
And also a database to connect all screening results automatically. 

 
20:59 
And for example, there is a programme for advanced instruments, I think Studios is called, which connects different platform automated platforms in between and keeps a database of all your data. 

 
21:19 
So as you see, automation can really help to ensure accurate data tracking through this lengthy workflow. 

 
21:28 
And a combination of lab automation, digital solution and analytic tool analytic tools appears to be the path towards the faster and more efficient outcomes in cell and development. 

 
21:44 
And there is no denial that technology has had a significant influence in on the development and applications of stable cell lines. 

 
21:53 
And it has saved the stable cell and technology as it is today with the introduction of automated systems to the platform. 

 
22:03 
I will give some examples of these systems. 

 
22:06 
I think a lot of them might be well known to you. 

 
22:09 
There are single cell printers which would ensure well succeeded with single cells and provide proof of monoclonality. 

 
22:19 
Then I one imager also provides further evidence of the monoclonality and monitors the clone confluence the VIP system which is a combination of the two mentioned above and provides a high efficiency single cell seeding with image based proof of clonality. 

 
22:38 
And Agilent Bravo is a liquid handler and performs a colony peaking routine passage and vector production and the Cytomat incubator in tandem with barcoded planes ensures that our actions are traceable and to achieve a screening of more clones. 

 
23:00 
At the same time. 

 
23:01 
There is also high throughput instruments, for example the Qiacube HT which is an automated 96 well played DNA extractor where can help you in your platform to increase throughput of clone screening. 

 
23:19 
And also the introduction of a mini bio reactor. 

 
23:25 
The number 15 as a final step in the screening process to kind of assess how your clone will behave in a production like environment and also evaluate media and feed selection. 

 
23:46 
And finally there are a lot of automated platforms for characterisation and stability of the producer cell lines. 

 
23:57 
For example, a DDPCR, QPCR test which is an automated Western blot for protein expression and the ELA which is an automated analyser. 

 
24:11 
And as a final remark, closing my presentation, I would just like to say that cell and development as a huge and rich history and a bright future and there are constantly new technologies and advancements. 

 
24:26 
And it at this point is just a wait and see where this will technology will go next. 

 
24:34 
So thank you very much for your attention and I think now we can move into our discussion. 

 
24:46 
So starting with our first topic for today about latest advancements in SL and development, new technologies and applications. 

 
25:04 
First question would be what new technologies are there and how have these advanced the field? 

 
25:12 
So Salice, maybe and you can start with your point. 

 
25:18 
Sure, Yeah. 

 
25:19 
Thank you for a great overview or presentation, Krishanthi, really appreciate that. 

 
25:26 
So you mentioned quite a good number of those technologies and one of those that I think good to take note of is one cell plate 96 well plate by I by biochips. 

 
25:42 
This is really good for those who don't have advanced, you know, instrumentation and want to proceed with, you know, doing single cell cloning without going through the traditional route of limiting dilution. 

 
25:57 
And with the plate you're able to have, you know, slots where you input your cell population and then you know, those are deleted, you know, to a particular cell density and you're able to obtain about let's say 20 to 30% single cell isolation. 

 
26:15 
The another technology that recently have been exposed is the cell raft technology by Cell Microsystems. 

 
26:23 
And this system actually relies on a cell raft array, which is a cell culture dish with about, you know, 10,000 to 15,000 micro wells in cell rafts. 

 
26:33 
And so this kind of you're able to have micro wells within a micro plate, which enables you to have cell to cell communication and allows the potential for, you know, better cell algorithm, especially for those cells that are very hard to single cell clone. 

 
26:52 
So that's, you know, a couple of those that I think would be great for our audience to do in addition to what you shared. 

 
27:02 
Great. 

 
27:03 
Thank you for your input, Martin. 

 
27:08 
Yeah, that's not really my speciality. 

 
27:11 
I'm a researcher at the university. 

 
27:15 
We don't use this high end equipment normally. 

 
27:21 
OK. 

 
27:22 
So you were doing the traditional limiting dilution. 

 
27:29 
Yeah, that's what we normally do. 

 
27:30 
Obviously our expertise actually is to establish drug resistant cancer cell lines. 

 
27:36 
So we adapt cancer cell lines to anti-cancer drugs in a very traditional manual way by continuous exposure to step wise increasing drug concentrations. 

 
27:48 
And our unique selling point is that we have almost 3000 of these drug adapted cancer cell lines. 

 
27:56 
So that's our main expertise when it comes to cell and technology. 

 
28:02 
OK, we have a question in the chat. 

 
28:05 
How is fully full automation AKA culture stations proceed by the community? 

 
28:13 
Is the higher throughput and minimal hands on time on the machine highly beneficial? 

 
28:24 
So I can start by saying yes, it is, it will minimise human error for soul. 

 
28:35 
It will allow scientists to run things in parallel and I believe also to elevate and minimise the timelines. 

 
28:49 
Yeah. 

 
28:50 
And I definitely agree with you, Christian. 

 
28:52 
The for instance, if you have a situation where you've got multiple clones and you're trying to isolate them and characterise them on the basis of growth rate and you know, stuff like that initially that really helps you to shortlist your clones. 

 
29:06 
Having, you know, automated counter systems like BioSpa citation definitely helps with respect to, you know, your reducing your manual manipulation of things to saving hands on time. 

 
29:20 
And also having, you know, something like the EQ site also does help with having more hands on time for other things for your cell culture flow. 

 
29:35 
Exactly what I would add is that automation is obviously good to reduce the human element, right? 

 
29:49 
The human variability. 

 
29:50 
We know this, that even if two very experienced people do the same experiment, you have a different outcome. 

 
29:58 
And if you, for example, an omics experience is known that you can identify the person who performed the experiments from the data that come out of them even and that across different platforms. 

 
30:12 
So this human element, although it's very difficult to narrow it down, if you want to have something that works consistently and again, if it's automatized, it is obviously much more reproducible. 

 
30:25 
Yeah. 

 
30:31 
So another question we have is what is the future of other expression systems other than chow and hex cells set as bacteria and yeast? 

 
30:42 
So I've worked with yeast in the past and what we were trying to do is to basically fight let's say the syncytia effects that the VSBG envelope was causing to the cells. 

 
30:59 
And the yeast was the great system to do that because they have the cell wall. 

 
31:05 
But I think this has been addressed with the latest and advanced the technology of inducible systems where you just, these are only expressed when you add the doxycycline into the system. 

 
31:22 
Do you have any other experience in that Solis or Martin? 

 
31:27 
Yeah, recently came across, for instance, the use of plants to express AAVs. 

 
31:34 
And that was really neat to see how others were improving upon what we already have for these traditional systems. 

 
31:44 
So that's an alternative. 

 
31:47 
People also use insect cells, right? 

 
31:49 
And I think it depends very much what you want to produce and for what you want to use it. 

 
31:54 
So I think the main advantage of Cho and heck is that they have mammalian post translational modifications, right? 

 
32:05 
And that makes a huge difference. 

 
32:06 
If you need something that looks like a humanoid, least mammalian protein, you will go for a different system than when you are after a product that is used for something completely different. 

 
32:22 
Yeah. 

 
32:24 
So maybe we can also address any automation gaps you think they will be. 

 
32:31 
There are currently in the workflows of the cell line development. 

 
32:49 
Any of you, I'm not qualified to answer that question, I'm afraid. 

 
32:55 
Yeah, Chris, So for instance, you mentioned I think the clone picks which is 1 and definitely in those workflows you might have your pleated cells in a matrix. 

 
33:20 
Think depending on what you want to identify, it might not work for you. 

 
33:26 
And so I think one of the other technologies out there is the cell selector and that's also antibody based, you know, high throughput screening of your clones. 

 
33:39 
I think if we could have a technology where if you don't have an antibody developed for your target of choice whereby you might have to screen by PCR, is there a way that you can actually screen in process? 

 
33:51 
I think that's something that would be great to see. 

 
33:56 
So more technology around analytical and development and assays that will characterise your cell lines better and will probably generate data to help you with sort listing and reaching to your top producer sooner. 

 
34:18 
Definitely like right now with the technologies that we have, it's working well, especially if you have you know, proteins of interest that are being expressed that you're looking at, you know, getting those identified earlier in your clothes that work well. 

 
34:35 
But when you're thinking about gene therapy where you are not really expressing you're put in at that point and you don't have an antibody developed to target that might be something with you know, having progress on in the field. 

 
34:54 
Another question is what are some major regulatory aspects that the field of cell and development? 

 
35:01 
So to consider for that, I think I briefly that's the monoclonality insurance requirements and the presentation and how you need to have proof of your whole well and your single cell from the day of the seating the next days to assure that there is only one single cell that has grown into a colony. 

 
35:30 
Any other aspects Martin or Celis? 

 
35:45 
No, I don't have anything to add to that. 

 
35:49 
Chris, something you could you re restate what you just said? 

 
35:52 
I think I missed it. 

 
35:54 
You want me to repeat the question? 

 
35:55 
Yes, about some major regulatory aspects in the field of the cell and development that we should consider. 

 
36:07 
Oh, I see that. 

 
36:08 
I think you mentioned, you know, the most critical of them with is being able to track your single cell clone, you know, from the day of cloning and you did show some nice images. 

 
36:23 
So I was wondering, you know, with you how have has your experience played out with respect to, you know, being able to fine tune that to make sure you always have it? 

 
36:36 
So there were a lot of optimization around methods and instruments. 

 
36:41 
So I mean like when I started we were doing the limiting dilution, but then with the introduction of the automation and testing the different instruments, we concluded on the VIP system that will actually combine the isolation of the single cell with a proof of image that the cell is there in the well. 

 
37:10 
Another aspect I would say in terms of regulatory requirements would be to have everything documented from the day you are starting your cell and development campaign from materials and lots of from media that you are using to full traceability of your cell line, your wholesale line and history and all the Co base and that they are needed later on. 

 
37:43 
Yeah. 

 
37:44 
And I really liked what you introduced about the studio system that is able to have, you know, a whole integrated system of tracking everything from beginning to end. 

 
37:59 
I think that was a good example right there. 

 
38:02 
Yes, I believe that system combines 3 different instruments. 

 
38:09 
The data are transferred like automatically and they are stored in a common like in A1 platform. 

 
38:17 
And then you can see like from the day that you see that your single cell, all the data which is actually quite nice to keep track of your clones and makes it much easier later on. 

 
38:35 
So another question is regarding automation. 

 
38:38 
Are there any public data sets available for improving TOE or HEXA lines to introduce mutations or changes in a rational way to optimise the production? 

 
38:52 
I don't think I haven't seen anything in that aspect. 

 
39:01 
Me neither. 

 
39:02 
Yeah. 

 
39:05 
There are high throughput CRISPR screens which have been done for, you know, heck 293 cells. 

 
39:12 
I'm thinking that might be closely related to what you know, the question is asking whereby, you know, you use CRISPR screens to see if you can screen for your gene targets that might help you produce your gene therapy product of interest. 

 
39:30 
And there are some publications to that effect. 

 
39:37 
Yes, there are a number of publications that show you how you can improve by certain manipulations cell lines, but I don't think there is a database that summarises all the information. 

 
39:53 
Yeah. 

 
40:02 
OK. 

 
40:06 
Maybe we can move into the next generation cell line development and what is what we actually all want to achieve higher titers, high production and insert their timelines. 

 
40:21 
So how would the automation and the new technologies would help to elevate that and to achieve this target maybe Solis you can start. 

 
40:45 
So with respect to the next generation this line development, I think you did mention a few things there, but what others have also looked at is where you're really looking at your target of interest. 

 
41:09 
If you're producing that protein, maybe the typical pathway might have been just doing, you know, multiple single cell cloning modalities to isolate the best clone, you know, screening those for the production. 

 
41:22 
And there are those who've actually done a comparison of your high producers, medium producers and low producers and determining what molecular pathways are activated as they went through like RNA seek analysis of the, you know, the transcriptome. 

 
41:39 
And through that we're able to, you know, tailor their specific gene modification that would give, you know, the maximal output. 

 
41:50 
So those are some of the ways that we can help in getting our next generation cell lines to produce more going more into the molecular biology and even the understanding the host cell proteins and things like that. 

 
42:09 
And folks are already doing that. 

 
42:14 
I think it's important to mention that this is largely still trial and error. 

 
42:18 
And it becomes a little bit more informed trial and error than it might have been a few years ago or 10 years ago. 

 
42:25 
There's a long way to understand with our, to be fair, our general understanding of what a cell does and why a certain 1 is a high producer and so on. 

 
42:38 
It's still very limited, right? 

 
42:42 
It is, it's all still correlation and it's not really the systematic understanding that we would like to have. 

 
42:51 
And it is a very complicated system. 

 
42:53 
Yeah. 

 
42:54 
It just takes a lot of time. 

 
42:56 
It is a complicated point and you can invest a lot of basic research in that before you have or without even having and you may understand much more, but you may not have this tangible improvement that you may much easier get with some tinkering around. 

 
43:12 
So like a point from both of you is to invest more in synthetic biology and to understanding a bit more in the molecular biology level or how these will maximise the production to invest more in that. 

 
43:31 
That's right. 

 
43:33 
And there are those who've also gone through the pathway of looking at small molecules and how that interacts with, you know, the pathways that are identified for the production of their gene of interest. 

 
43:46 
And so as Martin mentioned, you know, it might at this point, it might likely be the trial and error, but you actually see that there's more of the field moving towards a more of a targeted approach to really get maximal efficiency out of our workhorse lines. 

 
44:10 
And when in what states of the development workflow would you introduce that in the early beginning or as part of screening your clones? 

 
44:23 
I think it basically depends on what your, what you know, your throughput is. 

 
44:30 
If you are limited in personnel, maybe it might be after you've identified a high, low and medium set of producers and then spend a bit more time on those. 

 
44:41 
But earlier on, you know, understanding what contributes to the production of your protein of interest or gene of interest. 

 
44:51 
I think that's really helped in getting you to your target. 

 
44:58 
And it probably can vary considerably between different gene products that you want to produce, right. 

 
45:08 
So it's what might be very good for some type for antibodies might not be that good for something else that you want to produce. 

 
45:17 
So it is obviously I'm an academic researcher, I'm always very much in favour more basic research. 

 
45:26 
But I also appreciate that it's not always, when it comes to making money out of it, not the most effective use of money all the time and you're interested in the product and not that much. 

 
45:41 
Why? 

 
45:41 
Yeah, there is yeah. 

 
45:44 
There is always the focus to reduce the timelines and to maximise the production. 

 
45:50 
So might what might be the challenges for that, what challenge someone might face to do that to maximise the production in shorter timelines. 

 
46:10 
That always depends a little bit on the approach, right? 

 
46:13 
And it's always a bit a question of luck there because you can, as I said, you can invest a lot of time and basic understanding and it doesn't give you this immediate better output. 

 
46:25 
But you can also, when you try to understand your system better, pick a low hanging fruit and make a major step in the same way, but just screening more clones, looking through more different like experiments. 

 
46:46 
Basically, you may just by increasing the effort, find a very good producer, a very high producer. 

 
46:55 
But yeah, it is, it's a question what is long term? 

 
46:59 
I don't know. 

 
47:00 
I don't know what is in long term will be better more in depth understanding or maybe more efficient and more cost efficient broader screening. 

 
47:10 
Yeah, both can be the answer and to some extent I would expect it will always be a combination of both over time. 

 
47:21 
Yeah. 

 
47:21 
Can you, yeah, that I definitely agree with you Martin. 

 
47:26 
And also if you were you have a particular host line that you are working with, it's great to take your time upfront to for instance, just screen and say is this cell line single cell cloneable? 

 
47:44 
There are situations where you realise you want to go from the pool to the single cell clone and those cells would not easily single cell clone. 

 
47:53 
Then you have to do what Chris Anthony, you mentioned, you know, where you thinking of, Oh, do I have to use, you know, a matrix based approach where there's still communication between cells, but they are not necessarily touching each other, you know, or do I have to go through, you know, supplementation? 

 
48:09 
I like you mentioned. 

 
48:10 
And I think those are things that you can save time by doing those cell and evaluation efforts upfront. 

 
48:18 
And then that helps you know, understand your cell line and know how to manipulate it better. 

 
48:26 
OK, thank you for your input. 

 
48:27 
We have another question. 

 
48:29 
How can we better utilise early on assays that can assess tighter production as early as possible? 

 
48:47 
I guess this will be a part of the optimization of all the assays for the thorough characterization of the stable lines. 

 
48:59 
Any thoughts on that, Martin? 

 
49:02 
What's the least? 

 
49:06 
If you want to be earlier and if your cells determine how good they produce, you need to have more and more sensitive essays. 

 
49:18 
I guess that's the answer. 

 
49:20 
But yeah, I don't have a but idea. 

 
49:29 
It also depends again then on what you are producing, how sensitive your essay can be. 

 
49:36 
And then the question is if you have a very sensitive essay, whether that is cost efficient too. 

 
49:47 
So I don't really, you see from what me waffling around, I don't really have a very practical answer to that question. 

 
50:01 
So was the question with a few clones, how you can get to a manual producing clone? 

 
50:08 
Is that what it is? 

 
50:09 
So the question was how can we better utilise early on assays that can assess title production as early as possible. 

 
50:24 
Yeah, basically there looking at what is already published, it's a great help. 

 
50:32 
And knowing when to apply those assets is also a great help. 

 
50:39 
So for instance, if you're doing your stable cell and development where you've integrated your gene of interest, you could assess for the efficiency of your integration. 

 
50:50 
So for instance, your integration efficiency is, you know, say above 80%, you can already begin to use that pool as a proof of concept to train that assay to be ready for your clones. 

 
51:08 
So that then might help you then, you know, have a ready assay for a few clones as they come along 'cause you might have, you know, fast growing clones, you might have medium growth clones and you might have, you know, slow growing clones. 

 
51:23 
So it's if you can have that preliminary in high efficiency in your stable that might help you know, pre-empt to that process for success. 

 
51:37 
OK. 

 
51:37 
I think similarly to that question, we also have transgene agnostic analytics are definitely essential for rapidly identifying top clones, but scaling down these assets is often difficult. 

 
51:53 
Do the panel have any thoughts on the recent advances in cell line screening through non invasive imaging and utilising machine learning models to learn more about how your culture is performing while growing at small scale? 

 
52:12 
I do not have those expertise with respect to using machine learning, but it's definitely where the field is going and you've seen publications to that effect that it appears to help you know, get much more out of your cell and development workflow. 

 
52:35 
Yeah, I've also seen like 96 well played bioreactors with the with electrodes in the on the bottom to monitor cell growth and viability. 

 
52:50 
Don't really have any hands on experience on that. 

 
52:52 
But this as you said is definitely where the field is going to trying to scale down more but also have the appropriate assays to identify your top producers as fast as possible. 

 
53:10 
I'm still a little bit sceptical about the speed of progress. 

 
53:15 
Sooner or later I'm sure there will be something will come out of that, but the machine learning approaches or AI in general depends very much on what we can feed in. 

 
53:30 
And I was just struggling a little bit to see what exact data you would feed in to develop that. 

 
53:37 
So I could imagine it is a longer way to that this is becomes a general thing than we may anticipate at the moment. 

 
53:49 
I like because all predictions in the future. 

 
54:01 
There is another question. 

 
54:08 
OK, no question. 

 
54:12 
So, yeah, So what the other tools like for example, in my presentation, I mentioned about the piggyback, the transpose transposes and I think useable system. 

 
54:27 
So all these are basically new, let's say technologies to achieve production. 

 
54:36 
But any other tools that you might be aware that we have at the moment that will also help to elevate the stable cell line development? 

 
54:58 
Yeah, like most often they're not. 

 
54:59 
After you've done these manipulations, you realise that your cell survival might actually be a bit suspect. 

 
55:08 
And so having those technologies that allow better cell survival is always helpful. 

 
55:17 
And for that, I like the recent, you know, technology for the, you know, cell developed by the Cell Microsystems, the cell rapt technology. 

 
55:30 
I think that's one that can help, you know, situations where you've manipulated your cells and your cells might take a bit, you know, to recover. 

 
55:38 
Having them being able to talk to each other in a multi well format is definitely an asset. 

 
55:50 
Any input on that Martin? 

 
55:54 
No, nothing to add from my end here. 

 
56:00 
OK. 

 
56:04 
I'm just going through the questions on the chat at the moment. 

 
56:14 
There is another one. 

 
56:15 
During assurance of clonality, how do you track genotypic drift of the clonal population over time? 

 
56:31 
I guess you can, when it comes to your stability assays, you know, you can actually capture some information on that. 

 
56:39 
And then if it seems like your cells are beginning to show, you know, differences in growth rate and those similar, you know, passage cells are maybe having an impact on productivity, then that gives you cause to then look at what is happening, you know, genome wide in each of those passages and that might give some information on that. 

 
57:08 
OK, Martin. 

 
57:09 
Yeah, I would have rather returned this as a question. 

 
57:12 
I would have thought that you as long as the system behaves as it initially did and as you want to behave it or as you have establish it, you wouldn't really look. 

 
57:24 
I think the genotypic drift always follows the phenotypic drift, right? 

 
57:28 
If you see a phenotypic drift, then you look into the and whether something has changed. 

 
57:33 
Yeah, that's right. 

 
57:36 
So how would you like look if something has changed? 

 
57:45 
You mean, I mean phenotypically and then and the genotype. 

58:03 
I think the time is close to three. 

 
58:10 
So if there are any, not any other questions from the people joining on the chat, No, I don't see anything else coming. 

 
58:29 
So for that, yeah, I would like to thank you all for attending and Martin and Solis for your input and discussions and that was great. 

 
58:41 
Thank you. 

 
58:42 
You're welcome. 

 
58:45 
So thank you everyone for joining us today. 

 
58:46 
Thank you Christanthe, Martin and Slasi for joining us and sharing your knowledge and all the questions that come through on the chat. 

 
58:53 
I hope you have a good rest of your day and hope you can join us for another one in the future. 

 
58:58 
Thank you very much. 

 
59:00 
Thank you. 

 
59:02 
Bye everyone.