Karen Taylor (00.00.00): Welcome to Life Science connect: Deloitte’s podcast for the Life Sciences industry. This series features conversations with the leaders from across the healthcare ecosystem sharing their insights on the critical issues facing the industry today.
Hi, my name is Karen Tylor and I lead Deloitte’s Center for Health Solutions, an independent research hub that supports Deloitte’s healthcare and life sciences industry teams in their work. As always being able to meet industry leaders to discuss their views on the challenges that are affecting their businesses and exploring potential solutions to these challenges is a real privilege. Today I am joined by my colleagues, Kevin Dondarski, Senior Manager, Strategy & Analytics, in our US consulting team and Naveed Panjwani, Director, Strategy & Operations Consulting at Deloitte UK. Would you both take a moment to introduce yourselves. Kevin?
Kevin Dondarski (00:01:00): Thanks Karen. Kevin Dondarski, I am a member of our Life Sciences R&D strategy practice based out of our New York and Jersey office in the US. I focus my efforts primarily on helping companies think through R&D productivity issues and in how they can reallocate capital and think in an effort to try and drive better return on R&D investment. I have been with Deloitte going on 14 years now and before that worked in pharmaceutical R&D. Pleasure to be here.
Karen Taylor (00:01:24): Thanks Kevin. Naveed?
Naveed Panjwani (00:01:26): Hi Everyone. Like Kevin, my career has been sort of split between R&D roles in the biopharma industry and working on the transformation of R&D productivity in my consulting roles. Our focus increasingly tends to be on cycle time speed, as a means for greater productivity in R&D to gain and it’s been cycle time gains starting to materialise slowly which I am looking forward to talking about, as a part of this podcast.
Karen Taylor (00:02:00): Thank you both. So today we are going to focus on findings from our annual Measuring the return from pharmaceutical innovation report. This report is based on analysis of performance in 2020 and is the eleventh in our annual series. The companies in our analysis comprise the top companies by R&D spend. We have been tracking how they fared over those past eleven years and overall, the companies whose performance we are analysing has seen a decade long decline in projected R&D productivity reflecting the challenges that the industry is facing more widely. However, for the first time since 2014, in 2020 we see that the average IRR showing a small uptick when compared to the 2019 results. And our wider analysis suggests this may be a sign of potential reversal in the declining trends. While some companies seen a few impressive peak sale projections, they are still facing the rising costs of conducting clinical trials including on-average longer cycle times although we are seeing some improvements as Naveed just mentioned. In recent years we have also started to see the development of novel trial designs and improvements in efficiency to digitalization of drug discovery and drug development. The COVID-19 pandemic has highlighted the need for speed in clinical development to ensure that patients have access to safe treatments as fast as possible. But it is also seen an acceleration in the wider adoption of the some of the innovative approaches to the clinical trials. So, I am looking forward to discussing these issues with Kevin and Naveed over the next 20 minutes. So, let me start with a question for Kevin. Kevin, could you share what your top line summary of this year’s report is?
Kevin Dondarski (00:03:47): Yeah Karen, I’d be happy to and I think you have already articulated it. The top line message is that the broader R&D productivity has improved. I think it is important to maybe, before we jump into the numbers take a step back and just make sure that everybody understands what we are measuring through the report and so as Karen mentioned, we look at the 15 or 16 largest companies in the industry in their late stage pipeline. The late stage pipeline is really anything that’s in phase 3 or registration or earlier phases with breakthrough designation and what we do is for that basket or vintage of assets we maintain wide cycle commercial projections for their revenue potential and these projections are based on our analysts’ consensus forecast, in some cases custom forecasts and then we apply risk adjustment factors, company specific margin, and tax assumptions to really isolate the return piece – the return on R&D investment. And regarding the investment, we look at 10 years of historical cost data and use in industry cycle times, in phase allocation – assumption is to really estimate the proportion of historical costs that are attributed to that same basket or vintage of assets. And so, through that analysis which we replicate each year when we run this report, we notice that IRR last year was around 1.6 percent and it has improved almost by 4 percentage points to 2.25 percent this year. In the years of running the analysis, we tend to focus less on the absolute number given the aforementioned assumptions but rather on the change or the trend as being most insightful. And so seeing this positive take out is really encouraging. If we take that overall percentage and try and break it down one level deeper, if we look at the industry – by industry I mean the cohort of companies that we look at – if we look at the cohort of companies that we are looking at, the volume of assets or programs in the late stage pipeline has remained relatively stable – which is good news, in prior years we have seen that decline. And the average cost into bringing assets from basically discovery up to launch into the market has increased slightly but has remained relatively stagnant at USD 2.4 billion. But what’s really driven the change in IRR is the projectied peak sales process where we have seen a sizeable increase from 350 to 420 billion per program. It is really encouraging because that’s arguably the best proxy for innovation so to speak, it’s what the market is willing to pay for, and the increase in peak sales per asset is really driving the return around R&D productivity. It is also important to say that all this is despite obviously the headwinds that the industry and I guess the broader world has faced in light of COVID and it is truly something that if you would have asked me 6 months ago we wouldn’t have expected to see. So certainly an encouraging sign.
Naveed Panjwani (00:06:55): Kevin, I think importantly, let’s just clarify for business that the data that we are analysing in the past year doesn’t include much of the COVID period. So for those who are perhaps looking to see what the productivity signal or output has been of that disruptive period of the past twelve months or so, that is going to be reflected in our next year cycle, in next year cycle of analysis. It’s just I wanted to clarify that. But yeah I mean completely agree that this is the first time over a decade that we are beginning to see a reverse in this otherwise inexorable slide in return on investment in R&D. But, it’s also worth saying that if we breakdown the cohort of 15 or so companies, all but one, are still returning below the cost of capital for the industry weighted average cost of capital. That is still something for companies to consider and investors to consider that yes we are seeing an uptake, but we are still below cost of capital. I think another interesting thing to point out perhaps is that over the long-term we have seen the inputs into the development pipeline – new candidates and things that are in progress, in development, roughly balance out the terminations and approvals. So that input into the pipeline and output from the pipeline has broadly been balanced since we have followed these metrics over last decade or so. But this year, if we look at the waterfall diagram in the report you will see that new and existing components of the pipeline are actually slightly outpacing approvals and terminations, and therefore that balance of input versus output is slightly more favourable this year than it has been over the decade.
Kevin Dondarski (00:09:06): That’s an important point too Naveed. The challenge companies have always faced is not just delivering innovative products to the market but doing so in a sustainable way. And for so many years we have done this report, we have seen that companies one year have a volatile IRR year-over-year and so often it’s because of very successful programs exiting their pipeline and inability to replenish the pipeline with assets with similar kind of potential and so that's really encouraging trend as well from this past year without a doubt.
Naveed Panjwani (00:09:40): And to your point Kevin about the peak sales that on average these baskets of assets are achieving. Yes, there certainly has been a recovery as you say over the past cycle and that is a big contributor to the stabilization or even uptake of the overall returns. But I think it's important to point out that over the decade that slide down from the blockbuster drugs that were resulting in peak sales – 2 or 3 times what we see today that slide has stabilized, it’s not really a return to the original picture that we saw over a decade ago of where the original cohort to be followed or the extension cohort to be followed – where you know big general medicines type blockbuster indications were still in the realm of formation indications and still in realm of considerable peer pressure.
Karen Taylor (00:10:47): So Naveed, maybe you can say a little bit more about, you did mention cycle times, so could you perhaps say a little bit about what you could call the standout insights that you have identified from the analysis.
Naveed Panjwani (00:10:59): Just to clarify the cycle time measures that we look at are the time from initiating the first phase of clinical development to the time where the final pivotal study typically completes. And, in 2014, more than half a decade ago, just after six years cycle time and today it is almost exactly one year longer that we have gone from 6.15 – 7.14 an average. That is a topic that companies have been working incredibly hard to try and address. Many of our clients have looked to work on topics like cycle time for starting up a study, initiating patient recruitment, and getting closer to their predicted planned timelines for enrolment of that complete group of patients. But it seems that despite all of that effort, we are yet to see the fruits of those measures manifest themselves in these numbers that we are seeing. I think there’s a few different causes for that. One is the therapeutic area mix - so increasingly the industry has emphasized on oncology in the mix of therapeutic areas addressed. And oncology trials tend to be on average 2 or 3 years longer than a cardiovascular or metabolic disease trial. So as industry tilts more and more towards oncology that does drive up the study cycle times. The other thing is that even though retention and recruitment is a tremendous focus for the industry, it is still within a fairly finite and static pool of volume of patients. And so, more and more biopharma companies are competing to recruit and retain essentially the same pool of patients into their trials. There is an increasing need to get to a bigger group of patients in oncology trials for example depending on which study you look at somewhere between 2 and 9 percent of patients actually participate in oncology trials which is a very small number relative to the addressable patient pool. And industry needs to find more ways to penetrate that 90 plus percent of patients that aren’t participating in the trials. And I think it is fair to say that industry has started to employ greater automation, greater workflow automation and greater productive simulation, etc. to try and get better at during the mechanics the operations around starting the trials and executing trials and being smarter and predicting the enrolment hiccups they could anticipate the burden on the patient on how to minimize that. And I am confident enough that over the next couple of years we will start to see the impact of that on the cycle time numbers.
Karen Taylor (00:14:35): Kevin, what about you? What are the standout insights for you from the report?
Kevin Dondarski (00:14:42): Yeah. I mean I think there’s a couple. And some of them are similar to things that we have seen in years past. I think three things really. The first is I would say the continued proliferation of new modalities and so I think almost a fifth of companies pipelines are now assets that you know are attributable to some sort of next gen modality – you know what I mean by that is either oligonucleotides or cell and gene therapies or protein-based therapeutics. These are even things that we talked about as an industry for years and now you know they're starting to represent a sizeable portion of the industry late stage pipeline which is why and I think that it's not a coincidence and I think that coincides with the uptick in this year's numbers. I think the second is, in somewhat related but really the disproportionate dependency on external innovation. I think for years through the series we talked about you know the sources of innovation and how much of the industries innovation is coming either clinical organically or through externally licensed or sourced innovation. I think this year is up quite a bit another kick in the proportion of assets that are coming externally. I think some of that is to be expected when you talk about all the innovative new modalities that we're seeing in the pipeline. But it's always interesting trying to monitor because these companies continues to grapple with you know the proportion of capital to allocate towards external and internal innovation. And then I will say third, and we kind of laid out the report in this way but we have really seen a convergence in our two legacy cohorts. And so, when we started this report like 10 or 11 years ago, as we get older we forget these types of things, but we started with the 12 largest companies by R&D spend. And in 4 or 5 years ago, for you know midsize biotech firms who we thought had a different, really productivity profile that than the broader industry and we've really seen the IRR performance at peak sales, per asset performance and the cost of an asset to bring to market, we have really seen all three of those parameters converge across the two cohorts so much so that we are you know moving forward really just reporting a single cohort from here on out. So it's an interesting lesson in terms of the evolution of companies in the industry where as you know when companies jump onto the scene what was with the blockbuster asset or product, you know they are frequently under pressure to expand their portfolio either in new therapeutic directions or new modality directions and in doing so is hard and scaling is hard. And so, we have seemed kind of a convergence of the two cohorts, which I think is something many us predicted, but it is interesting to see that happen over time.
Naveed Panjwani (00:17:38): Yeah, it's interesting to think Kevin that these companies that had initially that narrow focus on one therapeutic area or even one disease area within a therapeutic area that as they have grown, they have also undergone more M&A and they have acquired integrated companies. Their processes perhaps have become more fragmented over time as a result and yeah it isn't inconceivable to think that the convergence between the returns of this extension cohort and our original cohort is partly driven by them becoming more mature biopharma companies with all of the baggage that brings.
Karen Taylor (00:18:19): So if I could just move on a little bit and Kevin you have mentioned the impact that the COVID pandemic has had on the industry and yes it's been in the eye of the storm throughout the past 14 months or so and largely for the positive things I put like the development of vaccines in a very short time and the discovery of other therapies that have some effect against COVID-19. We have, as part of our insights part of this report, we did look, we have looked at the impact of COVID-19 on the clinical trials development in general, not specifically focused on our cohort. And just wondered for you what has impressed you the most about the way pharma companies have responded to help their recovery from the COVID-19 pandemic.
Kevin Dondarski (00:19:11): Yeah that's a great question. And to me, I think it is agility and flexibility without a question. I mean so much has already been said about herculean efforts by subset of companies to develop either vaccines or innovative therapeutics to combat COVID. But we think about the industry more broadly, there's so much time and effort that goes into the clinical development phases of the lifecycle. They represent somewhere between 30 and up to 50 percent of the R&D budget and that's really where you have your heaviest allocation of labour and resources and you know it’s a complex endeavour on its own and the massive kind of halt on day-to-day activities that we all experienced similarly but really it was a wrench in the gears of the clinical development engine and so you know for years people have talked about alternative clinical development models and really reimagining how to conduct clinical development. And I think it's really to me impressive about how many of these companies in the broader industry did the best they could in the situation that presented itself to really deploy some of these innovative clinical development tactics and what I mean by that is moving from outside of the traditional model expectations coming to sites to more hybrid approaches. Leveraging virtual check ins or remote check ins for study participants using technology, like you can send mobile devices to connected patients and apps you know to collect patient data. You know in some cases delivering study product directly to patients. These are things that don't necessarily sound innovative in a vacuum but the fact that the industry was able to kind of take you know a compliance heavy environment take these things in it and really make the best out of bad situation. It is incredibly encouraging you know to move past COVID, just think about the evolution of clinical development and move towards decentralized alternatives development models, it's really encouraging to the industry. I think more so while a lot of these tactics helped companies, you know get their individual studies development programs back on track or keep them moving, you know I think what's impressive is the benefit that they provided. You know so some studies have indicated that you know there's a 64 percent of patients actually recorded have you know these tactics being more convenient and you know 52 percent said better real time data and insights into working and it's not just a these things are necessary just happening at the sake at the expense of quality but really for the benefit of the patient. So that one of the takeaway from the… The second that I would probably say this is really how, again despite all these you know complexities that COVID around world that it is really the emphasis on clinical trial diversity. It is an area which certainly has become a core thing for the sake of the industry and rightly so, with you know your clinical studies typically enrolling patients at a lower rate and you know their general prevalence in the population which are certain ethnicities and I think we saw you know we definitely did vaccine studies but some other studies really emphasis to really focus on specific sites in specific materials to check to really engage patients and enrol certifications from more diverse set backgrounds and ethnicities. And again, I felt I think this would expect to continue as we move as an important feature.
Naveed Panjwani (00:22:59): Yeah, I will just add to that Kevin. I think I see two broad impacts of the COVID pandemic. The first one which you called out is effectively moving from doing things in a very ponderous way where everything was done in it with the maximum possible that sort of effort to move into this more lean or more minimum viable kind of approach. And that’s manifested itself in a few different ways - for example faster approvals and initiations for trials we've had this move to for example, when I was reading in Italy that they've moved from doing that in COVID period from having every site have its own ethics committee approval to having one national ethics committee approval. When monitoring a trial there's now greater degree of state of verification performed remotely rather than physical site monitoring which consumes less time and effort. So all of these sorts of moves from what you might have thought of as maximum viable product or minimum viable product that is needed to get to a trial that's also bled into how you design the trial. So, for example, you know there's always been this tendency of the trial designer group to add a few extra endpoints to a few exploratory data gathering activities alongside the main endpoints of the trial and now there is a greater efficiency and leanness around the trial design as well. So that's one big area moving to leaner way of working. And the second big area perhaps is this idea that things don't need to be done in physical proximity to the patient between the patient and the investigator any longer. I mean there was already a move towards greater use of remote and decentralized clinical trial approaches, but this has been a big push to that way of working needed to become mainstream. I think previously everybody were thinking that I don't want this on my trial, it’s very good tried on different trial but not in my backyard. Now this is everyone's backyard where everybody is starting to become more comfortable with operating this way because they've seen it operating this way. All those things you talk about telemedicine and remote visits, home procedures, home supplies, etc., is becoming the norm. And one other thing that we tend to forget is this is not just being an effort on the part of the sponsors, it's also been an effort on the part of the regulator. I mean so it’s been a collaboration between regulators and sponsors to make these impossible timelines actually come to life during pandemic and I think that will leave a lasting legacy just as much as sponsors will be asking or a senior leadership teams within biopharma companies will be asking their teams to try and figure out what could be accelerated routinely from now on in trial start-up, trial execution, and regulate reporting. Similarly in the regulators, you know, within their walls those teams will be thinking well what can we change to carry over some of the benefits of our work during the COVID trial forward - are we going to be asking for a simpler dossier, are we going to be, you know, coordinating with the sponsor and sharing data with sponsor in a different way. So, hopefully those are all great signs for cycle times in future and productivity.
Karen Taylor (00:26:49): I think they're all really good ideas and good observations that we have seen and for me you mentioned that legacy, for me it’s regulatory legacy. I think, the one, that Kevin mentioned of getting more representative clinical trials to help more diversity and representation and the people are expected to take these drugs in the real world., is a legacy I hope to see coming from this and we are seeing very positive moves in that. So just on the sort of advice idea, do you have any advice that you would give to companies to prepare now for this new future of R&D and particularly in the use of new technologies and transformative approaches?
Naveed Panjwani (00:27:34): I think that's there’s perhaps three or four areas that jump out at me. The first is this idea that greater agility is not a risk, it's actually a necessity and it can be done. It's been demonstrably achieved of the spare time. So let's try and solidify those gains whether that takes the form of greater willingness to have digital endpoints, or to have remote collection of data, or whether it is around, you know, be more pragmatic with how clinical trial data is quickly analysed and reported, so you get to regulatory approval faster. All of those things, I think just need to be calm now and thought as normality rather than exceptional things which you do only on the odd clinical trial where you're willing to experiment with such approaches. The other thing that I think we need to do is start and initiate trials a lot faster. It’s, I think, quite an enormous cycle time waste that is experienced at start-up phase we have some folks that have cited 9 or 12 months period between the concept of a study being initiated to first patient being recruited. There’s absolutely no need really for it to take that long if companies have begun to do you start to move away from manual processes to a greater degree of workflow automation in that phase. You know, there are some companies who we work with who have managed to cut to half that aspect of cycle time. The other thing that comes to mind is that we are increasingly seeing greater pragmatism in the use of one stop source of data to our traditional randomized clinical trial model. The use of real world data for label expansions is now something that more and more companies feel comfortable with. The companies are starting to build real centres of excellence internally for use of real world data as a means of evidence to regulate that the drugs suffocation even beyond was achieved in a randomized controlled trial. Companies are becoming more and more comfortable, people and individuals within those companies become more comfortable working with that sort of data. It’s becoming more standardized and more manageable. Synthetic trials arms for example will be using placebo data from an industry pool rather than running a fresh placebo on each time those sorts of approaches I think are increasingly moving away from the realm of great ideas to being actual.
Kevin Dondarski (00:30:38): In my mind, I try to keep things very simple. In my mind, it’s that there is a lot of activities that we saw to combat COVID that were really focused on the patient and making it possible to continue pursuing clinical development in a patient centric way and I think it would be important to continue that trend as you move forward, not just view it as something that we had to do because of COVID. And I think that will help in a number of ways in accelerating trials, to expanding the outreach for clinical participants to even downstream activities like reducing patient drop outs and giving patients oral studies. I think it's important to continue with an eye towards these different tactics even once we get past the clouds of COVID, to be honest.
Naveed Panjwani (00:31:32): And, I am eagerly awaiting next year's data as I'm sure many people are. I am just eager to see how the industry has managed to maintain or possibly even boost productivity in this 12-month cycle. And indeed whether their therapeutic area mix and modality mix is going to change very dramatically given we now got an emphasis on vaccines in the pipeline like never before and we've got an emphasis on infectious anti-infectives in the pipeline like never before. So, I am really keen to see how it evolves next year.
Karen Taylor (00:32:07): Thank you. Yeah, I think we all are quite excited about that. It has been, as we described in the report a transition year for us, as we move out two cohorts into one combined cohort. But we also hope to add another few more companies to our analysis for next year. I just like to finish off by asking is that if there is one final message you would each like to give to our listeners to take away from our discussion today.
Naveed Panjwani (00:32:33): I would say keep doing what you are doing. It’s working. And keep doing more of what you can do because it’s working. We are starting to see productivity enhancements.
Kevin Dondarski (00:32:40): Yeah, what I would say is, you know, it is wonderful to spend, you know, half hour or an hour discussing with you Karen and Naveed. It's a topic that we can discuss for hours and hours and hours and so you know, certainly more than willing to and amenable to having evolved conversations anytime around the topic.
Karen Taylor (00:33:01): Yeah, I think this is a good place to finish. I would like to thank you Kevin and Naveed for sharing your insights, for the support you give to my team during the development of this report. And to thank our listeners for joining in with us and I hope they will join us again for our next episode of Life Sciences connect podcast series. And if you are interested in the report there will be a link to it shared with this podcast. Thank you very much for listening.
Kevin Dondarski (00:33:29): Thank you.
Naveed Panjwani (00:33:30): Thank you.
