Hi, everyone, and welcome. My name is Dorian Gifford, and I will serve as your moderator today. Thank you for joining us for today's webinar integrating CPV and APQR workflows to reduce redundancies. As your moderator, it's my role to ensure that we make the most of your time with us. I'm here today with Shetanshu Srivastava as global lead of implementation and support of analytical solutions. Chitanshu leverages his industry knowledge and data acquisition and analytics to design and implement solutions for complex pharma and biopharma manufacturing processes. Previously, he served as manufacturing science and systems manager at Doctor Reddy's Laboratories and a senior product application and business development manager at the software startup Simplify. Chitanshu holds a Bachelor of Technology in biotechnology from Velour Institute. Before I turn things over to our presenter, I'd like to cover a few housekeeping items. 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An on demand version of the webinar will be available after and can be accessed via the same link that was sent to you earlier. So that's it from my side. It's my pleasure to turn things over to Shetanshu. Hi Doreen, thank you so much for the introduction. So welcome everybody for the for today's webinar. I think today we'll be we'll be discussing the topic how we can integrate the CPV and webinar and APQR and basically see where the redundancies are and how we can optimize the process to make ourselves more efficient when implementing these ideas into in the organizations. So today's agenda is very clear. It's a very short presentation which basically covers 4 topics. In first topic, we are going to discuss little bit about CPV and APQR. Understand the nitrities of the CPV, CPV and APQR will not be going in the content of CPV and APQR. We'll try to cover more from the more from the workflow perspective and how we can utilize that information to build a solution which will be more effective for our day-to-day life. In second part, we're going to discuss the challenges with the current practices. Again, as I said before, the challenge not from the content perspective, it mainly from the workflow perspective and how we can make, make these combine these process to make more effective solutions. In the third part, we are talk, we're going to talk about our integration strategies, how we can use the technology and how we can do the optimization of in our, in our work flows in our process to come up with the solution. And in the last part, we are going to show you something from our side that once we implement the solution, how actually it looks like. So without wasting any of the time, I, I will start with the presentation. So first we're going to discuss about CPV and APQR. I think everybody in in pharmaceutical or biopharmaceutical world is aware about CPV and APQR. But I'll just very briefly cover what the CPV is. So the idea of CPV came somewhere in 2011 when regulatory came up with a guideline that OK, we we going to do the continuous verification of the process. So we have to implement certain strategy to ensure that our processes are consistently maintained. So ultimately we can ensure that the product which is going in the market is safe and good for the consumer. So in today's discussion, I'm my focus is more on the side of what do we do in, in CPV rather than the objective of CPV, because everybody who works in the pharma industry or biopharma industry has an idea what is CPV and why do we do that. But from the data perspective, if we see for the CPV, the important data which gets collected is about the CPPS which is nothing but your process parameters. Then the quality data which is Cqas or quality attribute along with that lot of metadata which also goes in the report. Something like how the equipment is performing, what is the environment in which we are doing the manufacturing, what raw material we are using and during the process is there any deviation or certain changes which has been implemented. Similarly, if you see from the APQR perspective, so APQR is nothing, it's a very, it's, it's the process which is always existed in the pharma industry. And these are the annual report of any product gets published where we basically talk about the the product quality, whether the product which is which is being created is of good quality and that gets reviewed every year. But as I said, the focus is not on the goal and the component focus is more on the data side of it. If we again monitor the data, we'll see there is a very clear similarity of the data which is being collected either for CPV or or for APQR. If you go in detail, even see on the APQR side of it, the data which is getting collected is same manufacturing data which is nothing but process parameters data, the quality data which is nothing but your quality attribute. Along with that there is an additional information in APQR gets collected which may not be part of CPV, something like customer feedback, some more detail about the supplier and the raw material which is being collected, information about the compliance information, regulatory information. So it is safe to say from my side that there is a very clear similarity in CPV and APQR or I can say that CPV is nothing but a subset of APQR. So with that little bit, let's let's go a little bit more in detail of the workflows of CPV and APQR. So if I talk about CPVCPV is nothing but third stage of process validation. Again, I'm not going in the detail of every step of how CPV comes up, but just from the workflow perspective. Initially when process get designed, it get designed on the process development side. Then the process is transferred to the manufacturing where the qualification happens which we sometimes call as a process validation. In process validation along with the validation, there is a risk assessment activity gets done which gives us an idea about what are my critical parameters, what are my key parameters, what are my critical quality attribute, what are my key quality attribute? And these all these parameters get recorded. And this helps us helps us design our CPV program or CPVSOPS as such. So we basically create every company has a different way of capturing this data, but you design an SOP which basically says how your program is be governed. And along with that you make certain additional document to capture information related to your control limits your, your CPKPPK and other things. So once your commercial manufacturing goes goes, CPV is a continuous process as the name suggests. So every cycle of manufacturing you collect the data. As as I mentioned before, CPV is about process consistency. So obviously the moment consistency and control comes in the picture, the idea of statistics comes in the picture. So the the moment we do with the production cycle or manufacturing cycle cycle goes, we collect the data, we do the statistical analysis, we calculate certain quality metrics or a statistical matrix, something like OTS rule violations, statistical rule violation, CPKPPAPPK and others. Depending on how your process is, all this information gets captured in the report. Along with that we capture certain metadatas like is there any change impacting this process? Is there any deviation happened during during our process? Are we doing any any risk assessment based on the process And all that information gets captured into our CPV report. And once this report, this whole thing gets done, the cycle ultimately gives gives us an output in the form of a CPV report which in organizations get archived and then we move on to next cycle. This process keeps going on for the whole life cycle of the product. Now again the frequency of CPV also depends on, it depends organization to organization, what product you are dealing with, what is the frequency of your production. But since it has a component of statistics, number of batches or number of lot plays a very significant role. So if you have a product where you are making 30-40 products every quarter, then the CPV reports becomes quarterly. If the 30-40 batches or 30 batches takes around six month time, it becomes twice a year or sometime on a small molecule side when you're in a in a month itself you're making more than 50 batches, then the CPU becomes monthly. So all these reports keep getting generated and keep getting archive in the companies. Now before I talk about any solution, any challenge, let's see the APQR workflow and then we'll go in the details and we're going to talk about the challenges in the solution as such. So on a very similar line, when we talk about APQRAPQR is an annual activity. And unlike CPV where the idea is to see process consistency, here the objective is to define the quality of product, whether my product quality is maintained. And it captures a lot of information other than process, other than process as such. So if I divide the the APQR into 4 component. So one is related to a commercial manufacturing, The other part of it is the product and process testing basically quality control. The third important part is the quality management system, basically quality metrics. And the last part is product release market. So whenever I have to create an APQR report, all these information which you see on your screen getting generated in different sections have to be compiled. Along with that the conclusion summary recommendation is added and that produces an annual product quality review, a document for me. And this is an yearly activity as the name suggests, annual. So now we have the clarity what is CPV and what is APQR. One thing which we can see that there is, there is some similarity, if not similarity, there is some overlap between CPV and APQR. We'll go in the details of these things once we go further in the presentation. So I'll move on to next and I would like to discuss the challenges in the current CPV and APQR practices. So when I talk about challenge in this presentation today, my idea is not to cover the challenge which you face from from the content perspective or from the science perspective. It's basically from the from the workflow perspective, the work which we which we do which is involved in in doing this. Let's get into it and see 1 by 1. So I have divided into two parts. The first part of the challenge is the redundant activity. As I said, there is a very clear overlap between these two process, so which ultimately leads to a lot of redundant activity. So if I go one by one, the first part of it is the duplicate data collection. A lot of time in organizations, there are separate teams who are taking care of CPVS and APQR and since they are separate team, they are involved in a separate activity of collecting these data. Again, my generalization is not applicable for everybody, but this is a trend which which we have observed over the time that people are separately collecting data for CPV and APQR. And when once you go and check the details, you'll find that the similar data is getting collected by two different teams. The second part is overlapping analysis. So a lot of analysis which happens in CPV and APQR is very similar. And since it is very similar, it basically leads to a redundant activity. Same control charts which I'm creating in CPV. When I go to do APQR, I create the same control chart. The third part of it overlap. So again, these are the component which exists in both CPV and APQR. And since they are the component exists in both, we end up doing the same process again. We do the analysis of those kappas deviation on whatever happens again. And 111 part of it is that we do the overlapping review. The other part of the problem sometime we end up taking a different conclusion of the same thing. Now the third and 4th part of the the redundant activity is the reporting we in the in the previous part of the presentation we saw that both these activities when we do at the end of it, they get substantiated by by a big report. So now since this report need to be need to be created, we end up creating these reports separately. These reports are very extensive, have lot of data, lot of information and so ultimately a tedious activity need to be repeated. Again. The 4th part is redundant documentation. Now by documentation I don't mean just the creation of the report. The repetitive reporting part takes care of the the creation part, but the documentation also include creation plus the review and approval. And we know that in a, in in pharmaceutical world, it's a, it's a very big and lengthy process of multiple stakeholders review and approval. Since we have a different documentation, it takes a lot of time to review those documents, approve those documents and ultimately archive those documents. And the 6th point is nothing but the combination of all of them. Since these activities are getting overlapped, there is a significant amount of redundant resource consumption. The manpower or the OR not just the manpower, even the, even the resource from from the technology perspective or or or or from any other energy perspective, it's getting repeated. We are doing the same activity again and again. So the same manpower, same resource can be used for a, for, for something better, some, some process optimization and other activities. The second challenge which we see on this side of it is from the data management and workflow inefficiencies point of view. So let's let's go in the details of it and try to understand it. The first challenge which we see is the manual process. Again, these are the challenges which I have which we kind of deduce from our side. It's some may be applicable for some organizations, some may not be applicable for a certain organization. But overall, these challenges exist in in our world. If when we when we go and talk to our customers, we realize very large amount of our customers, their data is still on paper. Now we know that both CPV and APQR is a reporting process requires the consumption of huge amount of data. When data is on paper, the collection process or become so tedious because when you do, when you make APQR, you need the data of a product for whole year and you don't just have one product, you have multiple product. So the whole collection process very becomes very challenging. Now somebody can say that OK, my data is not on paper. So how this is a challenging for me. So even if what we have observed that people have certain digital systems would suffice for them to create the CPV and APQR report because they again they have to collect the data from those digital systems manually. They basically have to take the data down, go to Excel or any other statistical soft. Now when there are certain organization where data is not on paper and they are in a certain maturity on the disconnect on, on, on the digital system where they have they have various distance solutions like they have limbs for QC, they have ERP systems, they have QMS system and and so on. But the challenge in those organization is being faced that when we are going to make these reports or when I'm trying to create CPU or APQR as such, I have to collate these datas from different systems. I go individually to those systems and get the data because these systems don't talk to each other. These systems comes by different vendor vendors. They do not have similar ontology. Even if I want to combine the data, it is a it is a manual process. Like for example, I have an electronic batch record from where I got the process data. I have a limb system from where I got the QC data. But I when I put those data together, it requires a significant manual effort to combine those data. So it's to start making sense to me. So it, it becomes a very challenging and tedious activity ultimately leads to the leads to a huge amount of time consumption when I'm when I'm going to do CPV or APQR or any other reporting for that matter. Now the third challenge which we have observed over the time, as I said, CPV is a, is a requires a lot of statistical analysis and the statistics is something or a statistical understanding is something is. It's not that it doesn't exist in the organization, but it's still. Is something need to be built more One of the challenges when we talk to our customers or even the team within, we found out that sometime they they face certain challenges with respect to statistical understanding and even if they implement certain concept, the interpretation becomes very challenging. So they're not getting the outcome which they seek out of the CPV as such. And OK, one more thing which which we have observed that when you going to use some rather simple solution, something like somebody wants to use Excel, some of the some of some of the statistical metric which is required to be implemented are more complex to to implement. It's not that easy. Even on top of that, the validation of them becomes very challenging. The fourth challenge which we which you have seen is about the reporting. Even though I have all the systems, I, my team is very well versed with statistics and everything is going found well fine. The reporting process is manual. The moment my reporting process becomes manual, the activity takes a lot of time. I have to sit even even I, I took certain, certain statistical software, created all the charts, whatever needed to be done. But now my team has to sit, open a Word document, collate all the charts, create a report, go for a workflow where everybody is reviewing it, signing it, which makes it very, very complex. Another thing which we have seen a very clear disconnect between either I can say CPV and APQR team or at least CPV and APQR activities. We treat those activities as separate. So they don't talk to each other. So they are not, they're not, they're not combining the overlay overlap as such to optimize the whole whole thing. So now when? So till now, we have discussed the challenges what we face. Let's see, we're going to talk about how do we resolve this. But before we go towards resolving the issue, let's understand more from our audience how, what, what challenges they are facing. So I would like to hand it over to Doreen for our poll question. Doreen, over to you. Thanks, Shetanshu. So our first poll question is what challenges do you face with your CPB and APQR programs? And you can select multiple answers. OK, Doreen, can you hear me? Yes, Yep. OK, I'll, I'll, I'll. Thank you for your answers and now. Back to you, Shi Tanshu. OK, so after this poll, poll question, I would like to discuss. We have discussed the challenges, we have discussed the problem. Now let's discuss how do we solve this is what? What is what? What should be our strategy as such to find the solution to this challenge? And is there any way we can we can come up with something which is more optimized, which reduces the work and gives us the similar output which I get when I do both the things separately as well as suffice the requirement of the industry? OK. So the first part which I want to talk about with the integration strategy, it's the need and the not not exactly need the role of technology. I feel we are living in the world of technology and technology can be a very big enabler for us to resolve any issues we have. So let's see what what role technology can play for us in integrating these two workflows and to resolve the issue for us. So first part, what we can do, we can. As I said, the first problem what what we had was about manual data collection or the data available on paper. So we first thing what we can do is we can digitalize the plant or digitalize my organization where the data is available. There are various available in the market which which will help me do that. Like if I want to digitalize all the data available in the QC, I can implement a limbs. If I want to digitalize all the supply chain, supply chain related data, basically from the APQR and CPV perspective, all the data related to raw material and packaging material, I can implement SAP or ERP system. If I want all the all the process related data, especially the trend related data, I can implement historian. If I want all the all the quality management data or I want to digitalize the whole quality management part, I can implement QMS. Once I digitalize digitalize this site, we know that all the data is available in the electronic system. So the next thing what what I can do is I can look for a solution which can combine all of them together and give me a single source of truth. Now somebody can ask a question, why if, if, if I can implement a data management system, why should I implement limb CRP or in QMS system? And which is a very valid question, but it is important for us to understand not everything is just about TPVAPQR or data, It's about the whole operation. These systems are very specific, they're designed for certain operations. So they and how they're maintaining, but we have to have a technology or a system which can combine the data getting produced in these systems. So we can have some kind of a data management system which can talk to these systems, bring the data together. And when I say bring the data together, it doesn't mean that it just pulls the data and dumps the data. It stitches the data in a way that when user sees the data or want to utilize this data, it's available in a ready to use format. And the third part, what we can do is we can do the workflow optimization. This is a very critical part and I feel it's the crux of this whole webinar that how we can optimize the workflow between the CPV process and APQR process. When we were discussing the workflow, we saw there is a, there is a significant amount of overlap or redundancy how two teams which are responsible for these activities, we can work together, find a process through which CPV and APQR can be, can be combined together. Basically CPV, APQR can be a by product of CPV activities or CPV can become a subset of APQR which fits very well in it. For that definitely we will need, we need collaboration between the teams that are responsible for it. We need alignment between the Sops, vistas which basically govern these activities. Also we need to see, we need to maybe extend the horizon of CPV to include something which happens in APQR and I may not be doing in CP right CPV right now. And this is something organizations can discuss between themselves, the the manufacturing or MSAT or QA experts can come together and design the whole workflow. Before I get into this, I'll just cover these points one by one that what do I mean by distillation of data? What do I mean by reducing the number of data island? And then we'll come to the workflow optimization. The next line of mine is about distillation the data. I think it's very clear from the slide itself, so I'll not spend too much time on it, but I just want to give a glimpse of that. When we when we talk about a manufacturing process, there are various areas where a significant amount of data is getting generated, like the people data, whether the person who is involved in the manufacturing activity has the right amount of training or not. All this information is captured in my learning management system. What is the status of my equipment, whether the validation is done properly, preventive maintenance is done properly, everything is under validation or qualification. All this information is available in my asset management system. What are the results of mine or quality data of mine whether it is maintained properly, what is the quality attribute or whether my all methods are validated? If all the information are available in the limb system. Similarly my enrollment condition in which I'm doing doing the development, all the building maintenance data is available in the BMS system. Similarly I have a QMS system. So these are the digital solutions as such which are already available in the market. They can be implemented to digitize data of different aspect of manufacturing. And the next part of it, once I have all these things available, I can go for a system which brings everything together. So I can have a data management system which sits in the middle, talks to all those system, brings the data, contextualize them and on top of that it has capability to produce reports which I need like CPV and APQR. Also it can give you the capability which is required in different aspect of my day-to-day life. Like I the same system can help you doing deviation analysis, process optimization. It can. It can have some advanced analytics tools which can make your process monitoring very effective or smart process monitoring as such. The same thing further can extend into prescriptive analytics and so many things. Because ultimately if I'll have the data available from all the facet, I will be able to take a good decision as an outcome. So once this aspect of mine is sorted, the next and the critical part will be about how do I optimize my workflow to to reach the outcome which I want to reach. But again, before I go for the interesting part of workflow optimization, I would like to hand it over to Doreen to have a poll question and post that we'll discuss about this, the integration or integrated solution as such. So Doreen, over to you. Thanks, Chachu. So here's our second poll question. What digital systems are you using for your CPV and APQR programs? A limbs, electronic batch records, quality management systems, integrated management system all. Of the above. Or none of the above. Thank you for your answers. OK, thank you everyone for your participation. And now back to you, Shetanshu. OK. So as I discussed before, we have talked about the data digitization, we have talked about how to resolve the issue of data islands and come up with a solution which provides me all the information at a single place. Now let's try to understand how we can integrate these two solutions or these two, these two things together through workflow optimization. So this slide was there before. I just brought it back again because this slide covers to very large extent what goes in my APQR. Now, if we try to understand how CPV is a subset of APQR, this slide becomes very useful. But before I get into the detail of these slides, you must be seeing two different percentages. Some are written in pink and some are written in blue. I'll just give a little brief description around it and then we'll go into the detail. So the blue, blue percentages which you see on the right side of it, they basically talk about how much a certain activity can be covered within an APQR. Like if I talk about the screen, that means if this activity, if I do in CPV, this can be covered 100% of APQR as such. So if I have to do the same activity in APQR and I'm doing in CPV, I don't have to do it again because it can be taken care of within the CPV itself. Similarly, if I talk about the blue one for that matter, like review of critical deviation in Kappa, very large extent if this activity can be covered in CPV, but there are certain part of it which may not be covered in, in CPV as such. So this, this a certain certain part of it may, may be left out when I when I do CPV. So that's why I, I have mentioned that 70 to 80% of it can it can be covered in CPV. Now the pink percentage as such, so I have I've done a kind of survey and spoken to a lot of SM ES to understand that when we talk about an APQR, these are 1015 different different activities or different type of information with gays and goes in APQR. And if I want to divide them into the percentage of APQR, what would be the right values? And after discussing with a lot of people these numbers I have come up with. But again, it's, it's not exact number, maybe it'll be different to different depending on what modality you're working on, depending on what product you are. But on an average, like if I, if I cover the review of critical process parameter and critical quality attribute, it takes care of around 40% of my APQR as such. And if I combine with my Kappa and change control, it takes around more than 50% of my APQR as such. We'll be clear about this percentage. So let's let's look a little bit more in detail that what all part how it can be covered when I do my CPV. Now see on the commercial manufacturing side, I know in my CPV I have to review my critical process parameter, I have to review my raw material, raw and packaging material. I have to review my qualification status of equipment. Similarly in my CPV also, I have to review my critical quality parameter. I have to do the review of the raw material and packaging material. I have to see the qualification status of my equipment. Now if I'm doing this activity in CPV, why do I need to repeat the same thing in APQR? So if you see this workflow very closely, you'll find the certain activities on different color or to certain extent. I am already covering during my CPV. So why don't I just just do the CPV and whatever is left, I just make the APQR in a sense I have to do quarterly CPV. I'm doing 4 CPV in a year. Whatever I have to capture in CPV, I'll capture in CPV. When I'm going for creation of my APQR, I just cover what is left from the CPV. So let's let's see the next slide which will give me give you a very clear idea will look like the moment I talk about my integrated workflow. As I said, CPV is a is a regular activity. It just keeps going on. Let's take an example that I'm doing a quarterly CPV. If I'm covering everything which required to be covered in CPV, I am left out with. But if you do CPV, you don't need to do the APQR because that's that's not true. There are certain activities which happen in APQR, which is not part of CPV. We don't discuss about market complaint, market authorization and those kind of things in CPV, at least in general, we don't do it. Similarly, stability of stability programs and review of the previous APQR, this all, all, all does not get covered in the APQR. But if we optimize based on the last, last slide, we'll realize that my 60 to 65% of the work which I have to do in APQR can be covered in CPV. So if on average, if I'm going to take a month to create an APQR, sometime it takes more if I'm going to take a month in APQR with my old processes, if I implement this strategy, you realize the time can be reduced up to 60 to 65%. Now somebody can ask question, it's very easy to say. It will be very difficult to implement and I totally understand it. So my idea was let's not just talk about it, let's try to show how this can be done. So we as an organization which has always worked to provide solutions to the Pharmaceutical industry. So we have, we kind of have a system or a or an application as such you can say which is, which is kind of dedicated to solve not just this problem, but this problem also. So we kind of based on this idea, we have created a system where you can create your CPV reports and you can archive your CPV report. You can create your APQR report and you'll have a way to combine the CPV and APQR report together to basically ultimately create an APQR. So let's see how the real output will look like, OK? So I'll, these are not just the words, I'll try to show you certain things from my side or certain screenshots of the application as such that how exactly integrated solution looks like. But again, before I move forward to show you a solution, we have a poll question and I would like Doreen to take care of this poll question and post that we'll go for seeing the solution. So Doreen, over to you for the poll question. Thanks, Shatanshu. So here's our last poll question. How much are your CPV activities integrated with your APQR program? A less than 20%, B more than 20%, C more than 60% or D not integrated at all. Thanks everyone for your answers. Hey Shitanshu, back to you. OK, so as I said, now let's look at the solution. So I'm just showing certain screenshot from from the application. What we have built from our side and this application is it's not just about APQR and CPV. APQR and CPV are one facet of it. It's a full-fledged data management system as such which can be utilized in multiple ways. But let's stick to the topic and talk about CPV. So in this application, since it brings data from all all other data islands, you can automatically generate a CPV report. Basically in certain clicks you can generate these these report. As such what need to be created. This report will be will be containing all all these statistical analysis related to CPP, CQA's data table and whatever is required as such for the CPA. Similarly you can within the same application you can create your APQR report. So if you see in my screenshot, you can create different sections and in these sections automatically data can be populated since all the data is already available in the system or it can be integrated to any other system. Data can all automatically be be basically brought in in these sections, right? You can. So the way it is designed, you can choose a specific section, you can push the data from within the application into the report or within this you can pull the data from anywhere outside. Like you have a certain QMS output or certain image at your site which is not available in this system, but you want it to be part of APQR. You can just pull it within the application or it'll become part of the APQR. And once you have covered all those things to create this APQR, you can go to your CPV report which you have created before and now you can push this CPV report directly into that APQR, the one the APQR we created. So the APQR previously had the had the information which I have not covered in my CPV. And later on I just push this CPV report directly into that APQR report. So ultimately I got an APQR report which has all the information which was not part of the CPV before along with that my four different quarter CPV report. So which ultimately gives me a complete APQR which is which has all the information which is required to be there. And this APQR either can be downloaded and pushed into a document management system or within the application itself there is a workflow for review and approval and can be done. So this system, this system can become your APQR archival system as such. So as I'm just trying to conclude from my side that there are there, there is a challenge because we have spoken to a lot of our customers and lot of leaders as such across the Pharmaceutical industry and they they do talk about these problems. I'll not say problem, but it's a current challenge. It's the, it's, it's something which some activity which requires an optimization. And we have realized some effort from the technology provider side and some effort from the from the organization to optimize the workflow can actually resolve, resolve this problem or can come up with a better solution, which we can see here. So with this, I would like to conclude my presentation. Thank you so much for being lovely audience and post this. I will hand it over to Doreen if you have any questions to be answered. Thank you so much. Thank you Shitanshu for this great presentation. Now it's time to answer a few questions that have come in from our audience. But before we do, I would like to remind you that it's not too late to send us a question now using the Q&A widget. We will try to get through. All of them, but if we run out of time, we will respond to individually. As a reminder, this webinar will be available on our website. Soon. All participants will receive an e-mail notification when it is available for viewing. Now back to Shitanshu, who will start answering questions that have come in. OK, Chitanshu, we, we do have some questions that have come in. Here's a question. How difficult is it to integrate CPV and APQR? At a site OK. Interesting question, little subjective also that how difficult or how easy it is. The level of difficulty definitely depends on what is the current status of us, to what extent the the data is already digital. And given all those things, even if even if everything is digital or on paper, it's more about the alignment between the teams which are responsible for these two activities. I think from the regulatory point of view, if I talk about already, there is an acceptance towards the idea and a lot of organizers are already thinking about doing it. And as I said before, it's not a binary game that yesterday you had no alignment and next day you just have 100% integration can happen. It can be done gradually. That a part of it which I was not doing in CPV. Now I start covering in CPV and whatever part I cover now, I'll not repeat into APQR and it can be implemented over the time. So it's not very difficult. It's just more about alignment across the teams. I hope it gives certain clarity that how it should be done. Yeah. So it also kind of touched on a regulatory question that I'm, I'm if we have. Time I'll come back to but. There's a good question here. Do you need to have electronic batch records to implement the software? No. So I think one of the image which I was showing you around the design of the software that the the way we actually design our system or we work for it, the system should be designed in a way that it can work in, in any level of maturity at your in your organization. You may have limbs, you may not have electronic batch record, you may not have QMA system. So wherever you have electronic system, the data can be pulled in wherever your data is on paper, the system should have capability to digitize that data. Basically it gives you, it gives you an interface to capture the data systematically. Even from our side, when we work on designing our system, we design our system where it can be implemented even in the hybrid scenarios where some data is distance, some data is not. And today you don't have electronic batch record, then also system works maybe after two years you have electronic batch record and then it can be integrated. So system is designed where at least the system which we are trying to design from our side, it can work for for an organization with 0 distillation to the organization which has everything which. Yeah, that was a great question. So we have another question and I'm just going to read it out exactly again. It kind of touches on regulatory, if we if we are not seeing any trends in CPP or CQA, are there any regulatory recommendations that we must do CPV? OK. So, interesting question. First of all, when you talk about CPV, we are not talking about one parameter as such. There are various parameters. You may have certain parameters where you're not seeing any trend. You may have certain parameters where you might see certain trend, but it's not just about the trend, it's about proving the consistency. You might have not seen a trend in a particular quarter, but you don't know what you're going to see in the next quarter and you will not determine this until unless you do this. So that's, that's, that's the whole idea that the whole idea is to continuous, continuous monitoring of your process. And the very subtle difference between CPV and APQR is ultimately we find out the same thing, but the idea of CPV is. To. Proactively check whether your process is consistent or not. And when I say consistent, it's I have to prove that it is consistent and that's where the statistical matrix comes in the picture. So as you said that what is the regulatory recommendation for me to do CPV, It's is basically to choose all your find out, do the risk assessment, find out all your CPPS and ensure that across different times or in whatever. You're doing your CPV, you are maintaining the consistency. Your control limit has reached to a level of stability. You're maintaining your CP case above 1.33, again, subjective, but above 1.33 to say that OK, your process is in control and various other other metrics like you do not have any trend rules as such. And even if you're having any trend rule, you have to have a either a clear justification for it or at least an assignable cost to justify why it is happening. Right, we have a another great question someone's writing in. We have manual registries. For the batch record. Right now for APQR we take the in process control and transfer them to an excel sheet to have any recommendations for us? Sure. So. Now Excel is one way of doing it. The challenge which over the time we realize that when we have, when we have Excel, it's with respect to first of all, data integrity, data validity and the, it, it brings certain certain difficulty in, in kind of doing the whole process. You haven't. So let's take, let's take a scenario that you have a, you have a batch record where everything is on paper. Whenever you have to do APQR, you'll be transferring on all the data to an Excel. Now the Excel where you are transferring the data, you have to ensure that the data is correctly transferred. Basically there's no discrepancy in the data transfer and you don't just have to ensure it, you somewhere have to prove it that there's no discrepancy in the data which I have transferred into Excel. Then you have to individually sit and create all the control charts for all the data you have taken. Then from that control chart you have to transfer to a Word document and then write the report. All these things can be automated where the same thing which you did for a month can be done with certain clicks. The only thing you have to ensure as your batch got done I just took the capture the data and captured in the relevant system or write system. It can be a data management system. It can be any other system which you are using. So because a lot of the activity which you are doing machines have our technology is much more capable and much more efficient to do that you have to ensure that your data is getting captured and rest all can be taken care by the machine. So there is nothing wrong in doing in the Excel. It's just the process can be make made much more efficient. At the same time when you're when you're facing any regulatory, you will be able to build more credibility with respect to your data. So you have you have to give less justification because you're using a system which follows 21 CFR compliant, has all the data integrity, the data which goes in somebody, one person is capturing it, one person is verifying it. So it just gives the confidence to regulate the assets. And if you ask my recommendation, yeah, just just I'm just if you, since you ask for the recommendation, if your data is manual, I would suggest look for a solution which can digitize your data and automate the whole process. So it'll it'll improve your efficiency immensely. There's been a lot of good questions around regulatory. Here's one that's at a high level. But what in your opinion is regulatory take? So regulatory agencies take on integrating CPV and AP QR. So. I have spoken to a lot of customers, a lot of QA leaders in the in the period of last one year and I have heard consistently from all of them that this is one of the thing which now regulatory is expecting. First of all, the expectation of regulatory is that you should be doing both in a sense that you have to have a very clear CPV program and at the end of a year you have to have an APQR activity, basically APQR document. At the same time, regulatory is also seeing when they go for the inspection, these two documents which come to their review assets has a very similar data and they're very OK, even encouraging towards the fact that don't do redundant activity, somehow integrate in a way that you're doing. It's basically doing CPV. And at the end of it, when I'm done with the CPV, I compiled the CPV together, added whatever needed to be added on top of that and make an APQR document. So regulatory at the end of it when they come for the inspection, they just review 1 document which has your continued process verification along with the information which is with goes in APQR. So we have time I think for one last question and you will have to have a short answer maybe how long does it take to validate that the system is GMP compliant? OK. Now depends on which system you're talking about, but if you take my opinion and talk to me about the solution, we try to build from our side depending on whether you're going for any external integration or not. If you take just a stand alone system which gives you a capability to manually capture the data and automate it, it goes from 8:00 to 10 weeks. If you're doing additional integration on top of this, depending on the complexity of integration, it just adds one 2-3 months time. But the basic validation of the system which includes your IQOQ and other things, 88 to 9 weeks is good enough to validate the system and good to go. Good to be used in a in AGMP environment. So you answer you answer that pretty quickly. So I'll this will honestly be the, the the last question and this kind of a broad question, but I think a good one. How can technology change how I manage my current? Process. OK, so if you if you see the process right now and I'm not just talking, I think I repeated this line again and again, it's not just about the content. If you. If you. Focus on the workflow of this whole process. Lot of things which can be taken care by the technology whether it's about other than the interpretation, everything else technology can take care even to certain extent of it. Interpretation can also be taken care by the technology because it can give you some very objective metric. In a sense, if you have a CPK number, you know through that you can deduce that whether your process is in control or not. Since a lot of these activities can be can be done using technology. Technology has a significant role to play. When I was showing certain screenshots, I was, I was trying to tell that the whole CPV and APQR, which I had to do for I had to if I was doing manually, I had to spend a huge amount of time to do this. But if I had my data somehow in my system, I would have done both CPV and APQR in a in a period of a week and week. Because I'm adding the time of writing the summary and finding the recommendation and all those things in future as we are moving towards the world of generative AI, if we embed that also in the system, even the interpretation and recommendation part can be reduced from week to days. Well, thank you. Thank you everyone for your questions. And if we didn't get a chance to get to your question, please feel free to e-mail to Tanshu directly. To register for future webinars or to access our archived webinar library, please visit our website. I would like to thank Shitan Chu for today's presentation and thank you, our audience for joining us, and I hope you have a great day. 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