Hello, everyone. Good morning or good afternoon, depending on, which part of the world you’ve logged in from. Welcome to this, webinar hosted by ABER Instruments, and thank you for joining us today. My name is Aditya Bhat. I’m the VP of technology at Abba, and, I’m based out of Alexandria in Northern Virginia in the in the US. We are presenting a joint webinar today. I’ve been, joined by doctor Madhavarao Chikkathur from the office of pharmaceutical research at the FDA. Madhav has a lot of experience with ABER capacitance and conductivity technology. This will obviously become quite clear when we get to his part of the presentation. Together, Madhav and I would like to welcome all of you to the webinar. Today, we will be talking about a very interesting and I and dare I say a relatively new, application, which is all about using ABER conductivity in, CHO cell culture to detect bacterial contamination early in bioprocesses. Just a few reminders before we start the webinar. The presentation should last about, say, thirty to forty minutes. We’ll keep, about ten to fifteen minutes for your questions after that. We do hope to get a lot of interesting questions after the presentation, so I’d encourage you to go ahead and, type them into the box provided on the platform. We will certainly try and address as many questions as possible. But, if your question is not answered mainly because of time constraints, we’ll be sure to respond to your questions by email. And as I always say, the most important thing is for you to sit back and enjoy the webinar. With that said, here’s the overview. I’ll open the presentation with a brief introduction to ABER. We’ll, then go through the technology, how it actually works, which will be interesting for those who are, slightly unfamiliar with the concept of capacitance and conductivity measurements. But remember, today, we are focusing more on the conductivity application. But, of course, before we get to that specific application, I will aim to quickly demonstrate some typical applications for which capacitance has been used successfully. And once I’ve set that scene, I’ll hand I’ll hand over the presentation to Madhur who will take you through the work that, his group has done at the FDA for early detection of bacterial contamination using ABER conductivity. And finally, when our, presentation is complete, we will move to the q and a session. Okay. So, let’s get started with a quick introduction to ABER. The ABER headquarters, as many of you probably know, are based in Wales in the United Kingdom. The company is located in a town called Aberystwyth. In fact, that’s where the name ABER instruments comes from, and this is where the technology was invented back in nineteen eighty eight, the technology that we’re talking about today. In twenty seventeen, we opened up a subsidiary in the US, and that’s where I’m based, out of Alexandria, Northern Virginia. Now ABER invented the use of capacitance to measure cell density in bioprocesses back in nineteen eighty eight. This technology is also called as dielectric spectroscopy. Capacitance, which is one of the parameters that it measures, is sensitive for the presence of live cells. Now we also offer the Optura range, which is our range of products based on bio reflectance technology, which measures total cells. Both capacitance and bio reflectance are complementary technologies. If you are interested in, measuring your total cell density with a technology that has a a wide linear range of measurement and also has non contact measurement options, please do get in touch. But, of course, today, we’re here to talk about, capacitance and more importantly conductivity. So we jump right into that. So how does dielectric spectroscopy actually work? What is the principle behind the measurement? As I mentioned earlier, this technology measures two parameters, capacitance and conductivity. Capacitance in very simple terms is the ability of any substance to hold charge around itself. But in contrast, conductivity is the ability of any substance to give away charge. Why these parameters are relevant when measuring cell densities? The answer lies in the structure of the cell membrane, the property of the cell membrane, if you will. The cell membrane, is impermeable with respect to charge, which means that it does not allow the free flow of ions across it. Therefore, under the influence of an electric field, and I should mention this that this is a tiny infinitesimal field that the ABER probe generates. Cells with intact membranes can hold charge around themselves and can hence act as, act as capacitors. So if you were to imagine a cell suspension, across, which an electric field is introduced using a positive and negative electrode, there will be a buildup of charge around live cells, and hence, each tiny cell acts as a tiny capacitor. Therefore, the more the concentration of life cells or density of life cells, the more the capacitance measured across the suspension. And the ions in the suspension, contribute towards the conductivity that is being measured. You can consider conductivity to be the concentration of charged ions in the suspension. In contrast, dead cells, which more often than not have leaky membranes with respect to charge, they do not have the ability to act as capacitors or in other words, they cannot hold charge around themselves, and hence, these are not measured. It’s for exactly the same reason that solid media particles, gas bubbles are not measured, since they cannot contribute to capacitance. Likewise, the technology also works with micro carrier cultures because, micro carriers, much like dead cells, do not store charge around themselves and hence cannot contribute to this capacitance. Same story with fixed bed bioreactors. Therefore, you you see capacitance being used regularly in bioreactors like the Isallis series. So what you end up measuring with this technology is purely the viable biomass of the suspension and the concentration of charged ions in the suspension. Now, I mean, the challenges associated with offline measurements are quite well known. With ABER technology, however, you are measuring your biomass in real time in situ. You do not need to take samples for the measurements. You’re not exposing your bioreactor to contamination risks. This measurement is also performed once every four seconds. So there is a lot of detail in the capacitance and conductivity profiles, which, then allows for timely intervention when required. Essentially, not only can you monitor your cell density and conductivity over over time, but ABER technology will also allow you to control something critical during the process based on this real time profile. So overall, you end up with a complete and detailed, picture or knowledge of your of these critical parameters in the process. So a quick recap, hybrid technology measures life cells since they can hold charge around themselves. It, also measures the concentration of charged ions in the suspension. Dead cells with leaky membranes are not measured. And because we measure the buildup of charge around live cell membranes, the capacitance is directly proportional to the total membrane bound volume of the cell. This is quite an important concept to to to mention here. So capacitance technology correlates with not just the number of cells, but also the size of the cells. Okay. I don’t want to I don’t want to take too much time talking about the applications with capacitance, but just to give you a a a quick taste, on the left, you have an example of batch fingerprinting in a step to mysis fermentation process. You can use this fingerprint in different ways, for instance, for real time troubleshooting. The graph in the middle is an example of a fed batch culture with NS zero cells where ABER were used ABER was used to track the cell growth. The dark blue line is raw capacitance measured in picofarads per centimeter. That’s the unit of measurement for capacitance. The light blue line is capacitance calibrated to read in cells per milliliter using a simple calibration factor or a lit like a linear multiplic multiplication factor if you will. The pink squares represent the offline type in blue count counts. Now this is a typical example of how a single frequency measurement can be used to track the entire growth profile of your culture. The dips that you see here at regular intervals, of course, represent the dilutions because of nutrient additions, which is quite correctly picked up by capacitance. The graph on the very right shows an example where ABER capacitance was used to, determine feed timing, which increased the product tighter by fifteen percent, one five. Just a few more examples. On the left, you have a graph from Biogen. This comes from a publication where scalability with the AbbaSensors was demonstrated from five liters to fifteen thousand liters. This work was done with two cells. In the middle, as I’d mentioned earlier on during the principle of the measurement, that ABER can be used with micro carrier applications quite successfully. This is an example where ABR capacitance was used to monitor the growth of baby hamster kidney cells on macroporous microcarriers. And, obviously, we can use it because, microcarriers cannot hold charge around themselves whereas live cells can. On the right, we have a perfusion application where avocapacitance was used as a part of an automated feed and concentration at a fixed value for a long period of time. Okay. So those those were some typical applications where capacitance has been used. And if you have any questions regarding capacitance, feel free to, ask me those questions in the q and a session. I will admit that dielectric spectroscopy is mostly and quite correctly, let’s say, known for its ability to measure capacitance because it it correlates directly with live cells, and it solves an important problem in this space, which is to measure biomass directly in real time and continuously. With that said, though, the AbbaProbe is definitely a two parameter measurement sensor. And over the years, we’ve seen conductivity being used in quite different and different and very interesting, applications. So let’s take a look at some of them. I, often say to the end users of ABER technology that capacitance will give you a biological fingerprint of the suspension. But in the same vein, conductivity conductivity gives you a chemical fingerprint of the process. So if you were to add acid or base to adjust the pH or see you would add nutrients in a fed batch application, you will see an immediate response in the conductivity signal. Therefore, you should be able to get a reliable and consistent conductivity fingerprint for your process, which can then be compared with your current process conductivity trend and activate troubleshooting strategies when required. Very similar to what you do with a capacitance fingerprint, as well. Now many users use the real time conductivity measurement measurement from ABER as an indirect estimate of osmolarity. Both osmolarity and sorry. Conductivity are influenced by the concentration of ions in the solution. Conductivity you can almost view conductivity as a proxy for ionic strength. Now there are finer nuances to keep in mind. For instance, conductivity measures the concentration of charged ions. Osmolarity, whereas measures the total concentration of all solute particles whether they are charged or not. Nonetheless, since conductivity can be measured by the ABER probe in real time continuously, it can prove to be a good estimate of osmolarity of the suspension. Another common use of conductivity is to monitor temperature changes during the process. Temperature and conductivity have a direct relationship where conductivity increases when temperature increases and vice versa. So keeping an eye on the conductivity fingerprint again will, will will help you make observations on, let’s say, temperature deviations in the process. This is an interesting one. Many of our customers utilize conductivity as an indirect indicator of cell free media quality. When you use the ABER probes, you can very quickly determine the conductivity range between which your media typically sits. Let’s say for your medium, conductivity is always around ten millisiemens per centimeter. You can then set a threshold that you work with, let’s say, between eight and twelve millisiemens per centimeter. If the conductivity is between this range, it’s all good. If it’s outside this range, that’s a call for action, because that can either mean that the Abbott probe is not functioning as per expectation or, equally importantly, if not more so, your cell free medium composition is atypical. And remember, you can do this, even before inoculation. So you have the opportunity opportunity to either correct it or stop the process before cells are added. So, yes, ABER conductivity can serve as an important indicator of, media quality. In both scenarios where you either acquire your media from an external source or you make your own in house. Yeah. Keeping a close eye on ABER conductivity is also useful way of checking the probe performance itself. ABER conductivity is always measured in its raw form in mili siemens per centimetre. It’s not converted to any other units. It’s not zeroed. On the other hand, capacitance is zeroed before inoculation. Capacitance can also be calibrated to read in other units such as cells per milliliter, but conductivity is always measured in millisiemens per centimeter. So this makes conductivity a very useful measurement from a, let’s say, from a real time pro performance check point of view. Troubleshooting, we’ve already discussed this, in in in in, previously, but it’s worth repeating, which is that the real time conductivity profile from the ABBA probe can be used for various troubleshooting exercises both in the process and for the system itself. And, of course, last but definitely not the least for this webinar to detect bacteria contamination earlier in your process. Madhav will take you through this application far better than I can. So, I will hand it over to Madhav. But before that, I should quickly mention that Madhav has already published this work, and this work has already been corroborated by another group at AskBio. So without any further ado, let me hand over the presentation to Madhav, who will talk about his group’s work. Over to you, Madhav, and thank you. Thank you, Aditya, for a very nice introduction. I think it it sets the stage for me to take over and then present our, new findings. New means it is probably new to the field, but, we have already published in twenty twenty one. That is the real time detection of bacterial contamination in bioreactor cell culture. So since I come from, FDA and from the office of pharmaceutical quality, I have to adhere to certain, confirmations of the specifications of the, office. So one is that that I belong to the pharmaceutical quality officer pharmaceutical quality, and, we have a mission statement. And here it is, everyone deserves confidence in their next dose of medicine. And pharmaceutical quality assures the availability and safety and efficacy of every dose. And, also, another disclaimer is that the presentation reflects the use of the author and should not be construed to represent FDS views or policies. Okay. So I’m going to give you some, brief introduction about, how the biomanufacturing, especially the protein therapeutics, enzymes, or proteins, or toxins, which are made. Even though it is, for majority of the people may know, but it is for those who are not very much familiar with this. So, usually, you would have a a recombinantly made cell line. It is a perpetually multiplying capable cell line cell. So that is also recombinantly modified to make the product of interest. That is it’s it could be an enzyme or it could be a monoclonal antibody. So that you’ll grow in large quantities and then store them in aliquots, in tubes or wells, and then store them in under liquid nitrogen conditions. That’s called a cell bank. So that cell bank actually provides you the source of this, product to be able to manufacture for perpetually. So you can store them for years together in the, in the liquid nitrogen conditions. So you draw one well. And from that, you inoculate that into a a shake flask or a spinner flask of about hundred, two hundred, or half a litre capacity, and then expand the cells. Let them grow in an incubator, ideal for its growth, and then go to a larger container, a larger flask, maybe one litre flask or two one or two litres in a flask. From there, if you have to grow in very large quantities, see some of the as Aditi already pointed out, it could be about ten to twenty thousand litre pass bioreactors, capacity. At that scale, you this is one or two liters is not sufficient. So then it goes to your bioreactor, a small bioreactor, about five liters or so. And then it goes to another twenty liter and then to fifty liters and hundred liters like that. There is a train that is called the inoculation preparation for the production scale. So this there is a train of these bioreactors are going to run, and then there will be one n minus one bioreactor, which is actually going to supply your c to the production scale bioreactor. On the right hand side most, the big one is your production scale bioreactor. So in all these, you will see a lot of probes there. Once they come into the bioreactor, there there will be a lot of probes to maintain, the production conditions like the pH, the dissolved oxygen content, the temperature, and additional probes like, for capacitance probe, but there ABER. And there may be Raman probes. There may be IR probe. So all these probes will be there that will continuously collect the data. And as we are doing production in this scale, in these conditions, it is a very complex and dynamic process. So you can see on the process variable side, there’ll be temperature, agitation, pH, dissolved oxygen, gassing, nutrients. All those are a few of them I have listed. And on the production side, also, there’ll be variabilities, like cell growth and its proliferation or multiplication and how you are going to actually control and monitor. And then there’s a cells are going to metabolize the nutrients in the medium. And there’ll be a consumption of the nutrients, and then there’ll be production of metabolic waste. And then there’s a synthesis of recombinant protein has to happen, and it has to be secreted. And then there is glycosylation and other post translation modification, which happens on the on the product. So the whole process is dynamic and very complex. And as such, compared to a small molecule drug, the biological drug is already complex. It’s a protein, and then it has got post translational modification. So under these conditions, as you can see, this whole process is at very time and then labor and cost intensive procedure. So we actually undertook a project to make, continuous manufacturing using a cell line, called v r c zero one. It’s called it’s actually made by vaccine research centre from the NIH. And then, they were they made this cell line to make a monoclonal antibody. It’s an IGG one kappa type monoclonal antibody. And this has been produced to make, produced to, or have the qualities of neutralizing several strains of HIV. But for our interest was that that we can whether we can use it just as a model because our interest is that how the process is likely to affect the product quality. That’s since it’s product quality, is our goal is that, product quality research. That is what we have always been focused on. So it is produced from a CHO cell line that is CHO k one cell line, and it’s a highly glycosylated, monoclonal antibody and is known to neutralize several strains of HIV. So that is the background of this cell line and the product. And here is a brief, description. This of this pictorial description of the, the methodology. In the center, you would have, the bioreactor. It’s about five liter capacity, five to six liter capacity. And then since we are actually trying trying out the continuous manufacturing, it involves perfusion culture. Therefore, we have two of these alternating tangential flow filtration systems. And these here are the filters. And then we have a feed medium on the right side, and then the bleed, bleeding bottle is there. That means to in order to maintain the cell concentrations at a known level, you have to remove the cells, so at certain point so that you will bring back the cell concentration to a a set level. And as you’re removing by, perfusion, by alternating trend tangential flow filtration, you will have to have to replenish the medium. And for that, you will have a feed medium here. In addition to that so we have all these, accessories for this, perfusion culture. And in addition, we also have a Kaiser Raman spectrometer, and then we have put a probe there to collect continuously the data. So this is the wave setup for us. This is our undertaking. This is what we wanted to do. And we have also implied an ABER probe, which measures both capacity, capacitance as well as conductivity as Aditya described. And we calibrated this in the medium of our interest so that we have used. So on the left hand side, you will see the graph, which shows that the blue dots shows there’s an increase in capacitance as the biomass, the viable cell density concentration is increased. And the white dots is horizontal line is the conductivity. That means there was no impact on conductivity as the cells are increased. The CHO cells have increased. And with this, we could derive an equation or we could relationship between the biomass and capacitance, use that to actually determine the concentration of the cell from the biomass, the capacitance that is measured. On the right hand side shows a typical batch run-in which the orange dots show that they actually measure cells, smell cell concentration in terms of VCD, viable cell density. And the blue dots, which is almost like a blue line since it is continuously, measuring the values, that is superimposed on to show that the ABER probe captures the actual viable cell density measure. To a great extent, it is comparable. And the the green dots on the above shows the viability percentage. As you can see, beyond sixth or seventh day, the viability falls off in a batch culture. And then there’s also corroborated by the decrease in viable cell density concentration. So with this, we have actually established that this ABER probe is suitable for our, experimental conditions. We also verified that by proportionally increasing the amount of the cells when we add it, whether the capacitance increases proportionally or not. The the blue the green bars on the left hand side shows on the that when you add five million cells per mil concentration, it is a jump from somewhere around point, five five or so to about close to about one point five level. Point two five to about, one point five. And then another, was added, and it went up to about roughly around point five to about two point seven five. So there’s a proportionally increase in capacitance is clearly visible when CHO cells were added. And then we also verified we added half the amount of that. There is about point two five million cells per mil. And then you could see that proportionally half the amount of raise in capacitance you can see. Somewhere around two point six to about three point three point six. And again, three point six to somewhere around, four point four or so. So there is a proportional increase in, capacitance is clearly seen when the chose cells were also added, proportionally or in in a known, volume. And here is the enamel run data. That means there is no contamination. No issues are there. What we have recorded. On the top, you see that there is a continuous capacitance measurement, the solid line shows, and then that follows a typical growth pattern. And the dotted line shows that of conductivity, wherein we have initiated some feeds like glutamine, glutamate, as well as some buffers were added, you can see a proportional increase in conductivity that is, indicative of increasing ion extract in the media. Whereas the growth curve as delineated by the capacitance is typical of the growth curve you see for a batch run. And in the bottom, you will see that the dissolved oxygen content, which is again that which is showing lot of variation, that dotted line. So that is typical of the, run data because as the cell concentration increases, and as it moves towards the stationary phase to the the decline phase, there’ll be the bad actor has to make a lot of adjustments to keep the dissolved oxygen level. So there’ll be some variation, but it will bring back to about forty percent level, by tweaking the flow of oxygen, the air, and nitrogen, and all those things. You will see those variations on that’s reflected there. And then the dotted and the dashed line is the temperature. It is solidly maintained around thirty seven degrees Celsius. And then the the the solid line on the top is the pH. It’s also maintained around seven. So this is a typical run. Typical data shows that that, there is no issues and capacitance is normal. Conductivity is normal. Whereas, since in our quest to actually make the continuous manufacturing, this perfusion culture, we started with, but we have actually had some setbacks. Like, that means, in within about two to three days, we found that there was contamination. So so this on the left hand side is one such batch wherein the we noticed by the thirty sixth hour after inoculation, the bioreactor has crashed. In in figure b, you can see that the dashed line is the pH the sorry. The dashed line is the d dissolved oxygen content. It hits the rock bottom because the bacterial growth is so high that the back the bioreactor is not able to maintain the dissolved oxygen content at thirty percent level. And but whereas the pH and the and the temperature are all fine. PH temperature, it maintains thirty seven degrees Celsius. No problem. The pH is also maintained at around seven because it can keep on adding the base to decrease keep to maintain the pH at around seven. So on the top, what we have noticed is that there’s a capacitance is gradually increasing, indicative of, somewhat growth initially of the two cells. But we have noticed an abnormal increase in conductivity shortly, and, that is that has no correlation with any additions. And this on the right hand side, you will see another pair of graphs, c and d. Again, the same thing noticed. Here it is within ABER about six to seven hours of inoculation, you notice that the bariatric crashed, and that the the we are unable to maintain the dissolved oxygen at thirty percent level. Whereas the same thing was noticed where the capacity capacitance in the c is solid line, the dark line, is steadily increasing, but not too high. Whereas we have noticed the conductivity sharp increase in conductivity very early in the, in the phase of direct run. So this is what we have noticed, and we also noticed in two more runs like this When we looked into, where the contamination has happened, where we have suffered the, the bar ABER reactor has crashed. So this gave us a suspicion that there is something is happening in the in the, capacitance, is the the the conductivity is indicating something else. We have confirmed by, gram straining that in each case that either the bacterium is grown, either a gram negative bacterium is grown or gram positive bacterium is grown. You can see on the left hand side of the picture is the gram negative rods. The right hand side, you have the gram positive cocci. And we wanted to actually to start. Is it actually the bacterium which is causing this abnormal increase in conductivity? So we took the actual bacterial suspension, and we titrated in the medium and to see whether it leads to actually increase in conductivity. So as you can see, when you are adding the bacterial cells, you can see the test one, test two, test three, all the way up to test seven. We are actually known amount of bacterium is added here. The capacitance is almost flat. Doesn’t change. See, on the right hand left hand side, you have the capacitance in figure a. It is point zero one to point zero five, and hardly there is point zero two units of change in capacitance. Whereas on the conductivity side, you can see that it increased from point two point zero two to two point one six, almost tenfold increase in conductivity. And, also, it is proportionally, it is responding stepwise. And we actually continued. This this one on the right hand side, you will see the same thing. Capacitance, there is no change, whereas conductivity shows the increase. And if you use the same spent medium, divide of the bacterium, there is no increase in conductivity. So spend the spend spent media spikes were, given. The conductivity also stayed put just like capacitance. So this actually led us to do more experiments and to delineate whether or not that this capacity is correlated with the bacteria, amount of the bacteria. So we have performed, four to five sets of experiments. In the first, we have added about one point one point five billion cells. And you you notice that consistently about the same level of change in conductivity you see. That is within the error experimental error possible. And the rate of change is also comparable, and average conductivity change is also zero point zero zero eight millisiemens per centimeter. We increased we doubled the concentration of the bacteria. You can see that the average conductivity changes to zero point zero one four, and we tripled the concentration in the experimental set, and, you know, the the where where four millis added. So it went up to zero point zero three zero. So it is proportionally increasing. The change of conductivity is proportional to the amount of cells. In the in another set of bacterium, we took it. These are in in in five mil when the five mil is added, another, stock of bacterium. You You can see that about roughly around three billion cells, it yielded the same zero point zero one five, millisiemens per centimeter in conductivity. So the average rate of change that is millisiemens per centimeter per hour was also found to be proportional to the amount of the bacterium added. Point one six nine for one point five billion, point three zero two for about roughly three billion, and about, for six billion is almost more doubled more than doubled in fact, for point seven four two, millisiemens per centimeter. And, again, you can see that even the different stock when it is approaching about three billion cells per mil, you will see about point three, sim millisiemens per centimeter per hour. Again, the ratios were also comparable, and the average rate of change, that is millisiemens per centimeter per hour per billion cells was across different experiment. They were comparable within the era. That is about point one to point one one, millisiemens per centimeter per hour per billion cells. So this indicated that it is the bacterium concentration that is the contamination within the bioreactor in the run is actually leading up to the increasing conductivity. So this is this was this whole, you will see even more, in this paper. It was published in twenty twenty one in biotechnology journal. And, Caitlin Morris, now she’s an assistant professor at the University of Massachusetts at Global and, professor Yule. They were also in the lab at that time, and then they participate in these experiments. So to conclude, these contaminations are costly for manufacturing. As you can see that in a real time manufacturing, condition, it is it starts from one while, and it goes all the way up to about fifteen, ten to fifteen thousand liters of bioreactors. It goes through several phases in between. And if the last is proportional to the detection time of the contamination, if you can do it early in the phase, you can stop right there, and then no need to actually waste the rest of the, you know, train, and the time and the and and and the effort. And the correct current detection methods involve offline measurements like gram staining, and they can delay contamination detection. Real time detection of contamination, it definitely enhances, the manufacturing. Futura ABER probe conductivity data for real time detection of contamination. It’s this this report is novel. But there there were actually some old data is there where they have, correlated some con you know, live cell bacteria to conductivity changes. It was, but not in bioreactor setup. So there are significant opportunities for biopharmaceutical manufacturing, in food manufacturing, cosmetics, and other liquid processing industries. This this application is there. That’s what we believe because, contamination is is not welcome in any of these, industries. And if conductivity can detect changes, which act which cannot be attributed to a change in concentration, addition of the salts or any other known ingredient, this this can be actually an indicator of something else happening, maybe contamination that they can consider. So with this, I would like to, close, my presentation and, ABER and for, you know, sharing this, webinar. And, here in Kate, as I said, Caitlin Morrison, they were they they were, or a fellow and a visiting scientist at our, FDA at in Silver Spring, Maryland, in our labs. And then, that led to this production of this work. And with this, we are open to questions.