Session Notes: From Project to Portfolio: Building and Shaping a Product Pipeline

Apr 22, 2026
From Project to Portfolio: Building and Shaping a Product Pipeline - Transcript
00:00:00
 
Vera Örså: I know everyone. I glad you have a lot of things to discuss which is a good start for networking and also for the next breaks. Uh I want to keep the agenda on time because people tend to leave halls. So with this I'd like to introduce Evan. Kevin, you had uh Kelvin, I'm sorry, Kelvin, you had a lot of um roles and artists CSL and Max Roto did the incredible courageous thing of founding your own biotech in neuroscience. I think what Daniel together which is incredible and definitely want to learn more about and you will talk about building and shaping the product resilience. Great. Thanks for Yeah. Oh yeah. Thank you. Yeah. Good morning everyone. Real pleasure to uh see you here. Pleasure to be here. Um personally I'm I'm here to share to learn and to connect with people. So those are my transparent objectives. So the first part of that is I guess on the sharing side. Um so what I'd like to do today is um talk about three main um things.
 
 
00:02:00
 
Vera Örså: Tell you a little bit about the journey I've taken and what I've learned on the way in this field of project portfolio management. the insights I've uh developed and um thought about again and again over many years over time. Then I'd like to talk um a bit about the theory of um building a product pipeline. So portfolio management in particular more so than project management, but these two are very related subjects. and then finally talk a little bit about the startup I'm now working on and how I'm applying those lessons and insights that I've learned on the way some of the theory into the practice of building an R&D uh pipeline. So to start with um yeah insights from my journey uh so far um so like many of you I'm a scientist by training structural molecular biologist I've studied uh um molecular mechanisms of neurodeenerative diseases long time ago in various academic institutions and then moved into at that time into consulting so spent some time with McKenzie working on R&D productivity already in post merger integration farm etc. Um even back then I formed my first biotech startup uh also focused on neurodeenerative diseases.
 
 
00:03:26
 
Vera Örså: Uh so to accelerate a bit more from there I moved to Switzerland, worked in venture capital for a while then moved to big farmer at Mount Serono in Geneva. um back into consulting uh and then uh that that business was acquired by PWC and back into pharma uh across to uh uh uh Sensign and then finally CSL before uh joining Emporium again. So this isn't exactly a linear path, right? Not something you would plan in advance. And I look back and think why the hell did I follow this journey? And I realized three key reasons. Partly, it's ADHD, right? I just can't I get kind of bored with focusing on the same thing unless I feel I can uh learn or continue to make an impact. Um um part of it is I still haven't figured out what I want to do when I grow up. Um and uh but the other part is really about curiosity. It's about understanding the business of innovation um and how capital allocation can be used to promote uh value creation for society and you can only really do that if you take multiple different perspectives.
 
 
00:04:43
 
Vera Örså: So this has been really a part of a learning journey and that's what I want to share with you today. So, some of you may know uh me from uh or at least the articles I published a few years back because it rattled a few cave. Um, I've published a couple of two-part blog on where the pharma industry is going. Um, really analyzing the diminishing returns on R&D productivity. Um, so these are published on my uh, LinkedIn page and and actually appeared also in Endpoints magazine. Um, it was actually one of the most popular articles or the most popular article ever in endpoint magazine until a week later when Vas Narisman um post his scan with uh Storm's connection with Stormmy Daniels and Michael Cohen etc. But thanks for that. Um so one of the insights in into this looking across uh farmer R&D productivity is that we are undergoing a long-term trend of diminishing returns in R&D for fundamental reasons not because of the symptoms that people talk about like tougher regulatory aspects and and and so on.
 
 
00:06:06
 
Vera Örså: It's literally a fundamental law that as we um over time uh generate new drugs and address clinical needs, the incremental room to further improve on those becomes less and less and it becomes harder and harder to do so. So the result of that is that over time we add less value per enemy. Each new drug raises the bar for the next and it also gets more costly to discover something that is better. And when you put those two together, you get diminishing returns. And it's a bit like in the oil industry when you exploring for gas and oil resources. You know, 100 years ago, you would poke your finger in the ground and oil would gush out in huge quantity and quality. Um and then as we exploit those resources over time um we have to dig deeper um and or find smaller pockets or or of lower quality and and so this is a I think a helpful analogy to think that it's as we're exploring um better uh treatments it gets tougher and tougher over time.
 
 
00:07:24
 
Vera Örså: Um and you can actually map this just by randomizing um opportunities. So value of opportunities versus cost of finding those opportunities. If you take any random distribution of opportunities in terms of value and cost and just simply plot them um as a ratio you and and then prioritize them. So put them in order of uh what is the better return on investment and then leave the later ones for the uh lower return on investment for later. You will naturally by prioritization get a a diminishing return on investment over time. And the consequences of this are profound because as as returns on R&D investment uh diminish this puts uh pressure on reducing uh revenue growth over time and there'll be a point where revenue growth or and we see this not just in pharma but across the whole world economy in terms of uh GDP growth. So this is a fundamental trend uh that revenue growth stagnates and uh could ultimately turn negative and then since R&D investments come as a fixed duty a fixed uh portion of the revenues we generate you feed that back into the cycle you've got less investment going in potentially um in the near future because of the diminishing returns and and this could be a you know a vicious cycle.
 
 
00:08:58
 
Vera Örså: The good news is this happens within every industry. Every industry ultimately gets commoditized and find it difficult to um incrementally innovate. Then what happens is industry new industries are formed, industries transform into another industry or a completely new new business model. Um and one of the one of the overriding kind of limitations to uh farmer drug discovery in development is in the target discovery space. Um you know we've got around 20,000 genes uh pro uh protein um coding genes in the human genome. About 3/4 of those are deemed uh not relevant to disease. there's no mutations which are uh associated or connected in any in any clear way to disease. This may be a slight overexaggeration with you know as you do more AI and pattern recognition we might find a few more over time but the signal to noise decreases and it becomes less and less reliable to find uh new targets. Meanwhile in the in the those targets which are clearly associated with disease many of them we've already explored and tested. Some about a third of them have already um uh translated it to new drugs.
 
 
00:10:23
 
Vera Örså: Another third of them never have and probably never will. And then we're left with these slight tiny slices in the middle where you can kind of predict uh how many of those may translate into future new drugs and how many of those were won't. And it's a very small slice indeed. And one of the implications of this, as you've probably seen, is that the competition around certain targets is becoming so intense. Now we're up to around 200 or more projects per target in development at any one time. And if you think about the the destruction in value of duplicating um the same approach usually with similar modalities etc. It's an entire it's a a crazy waste of resources. But also on the other side with this competition you know usually you will only get one or two winners coming out of each approach. um and the rest will either get nothing or you're anyway sharing the jackpot uh of commercial value with more and more competitors. And again, even worse than that is you usually won't find out who the winners are in the space until phase three or even in the market.
 
 
00:11:42
 
Vera Örså: So, it's an incredibly risky approach to have this level of targetbased competition and yet this is the route we're going down. Um so my learnings in this journey are conversely stop following the crowd. You know be bold, aim high, think big and different just for the sake of it. It's almost like if you're buying a lottery ticket. Bad example I know because the net expected return is is negative there. But imagine if it was positive. What we're seeing now is everyone picking the same lottery number. Herd thinking, her mentality, thinking that lottery number is safer because everyone else is doing it. All it means is you're duplicating the cost of buying a ticket and we'll end up sharing the jackpot. Again, it's it's a crazy way. So, just be different for the sake of it. Uh another key sort of insight is to challenge dogma to ask the right questions um um challenge your own assumptions uh and really explore the known the unknown. This is about learning. It's about exploration.
 
 
00:12:49
 
Vera Örså: It's finding things that no one has found before. And there also lies the danger of AI which is always based off existing data. um it it it's not very good at extrapolating into space for which there are no current existing data points. We have to keep science at the heart of this. Um but in doing so we need to focus and fail um cheap and fast. That's not the same as a kill early strategy. Actually, it's more about seeking the truth, asking the right questions and then finding out whether the uh the answers are positive or negative. But more important than positive or negative is is finding the truth. Um and this is a challenge in in business and pharma because business often rewards um positive results whether or not they are true or false. Whereas true science is really about aiming for true results whether or not they are positive or negative. And this can be I think one of the biggest wastes in in capital allocation are projects which should have been um have more uh rigorous experiments um set up to to challenge those and to have clear decisions.
 
 
00:14:10
 
Vera Örså: Go no go. But often we end up with ambiguous gray decisions and then trying to retrospectively explain why they could have should have continued post hoc analysis. Um and many projects will zombie projects I call them will continue um and and fail to get terminated but in the end they they uh very rarely if ever succeed the market. So seeking the truth is uh almost perversely um a more efficient way to do this. Just want to check the time. I think we're running quite okay. So now I I want to talk about the theory of portfolio management a bit and this is more directed to biotech but equally to farmer companies that are uh currently shaping in the process of shaping their portfolios which is an ongoing process. Um but really if you're a small biotech often you start from a single project. Um you may have some backup projects uh planned etc. But the qu the big question is whether or not to build a pipeline. And that's the first key decision to make if and it's all well and good having a project maybe one or two backups and saying that's all we're going to do and that's our contribution.
 
 
00:15:27
 
Vera Örså: Um but if you want to go on and kind of be a bigger more sustainable company or have more to offer you know you've got to give it some conscious thought about um what that pipeline you you will build will look like. So you know portfolio management, project management can be extremely complex. There are so many different factors to consider. Um especially when you consider the interconnectivity between all these different factors. Um complexity I saw as one of the biggest challenges in there. So simplification is a really really you know key thing if you're in into strategically shaping your portfolio making decisions keeping things as simple as possible is is absolutely critical. Um a good framework I'd like to there's a couple of frameworks I'd like to kind of uh introduce that that help to keep that possible. One is the balancing of objectives, opportunities and constraints. So for example uh we have some objectives uh listed here that um you know strategically companies may not just be all about shareholder profits etc. There can be other more qualitative uh strategic objectives but being clear about those up front is is important.
 
 
00:16:51
 
Vera Örså: And then likewise you know you can look at the different opportunities uh the different decisions you can make in shaping a portfolio and uh and management constraints which are you know what we you must not do or can't do sometimes you have legal contracts in place that you can't take certain options partnership agreements etc. So framing things in this this way can be quite helpful. Um another framework um that is uh helpful. So the optimal portfolio would be the sector. Another framework which is uh helpful is a sort of even higher level um less sort of mechanical maybe more philosophical which is why the company exists what it's what its uh purpose is what it's there to do um and how that relates to the capabilities what the company's uh good at uh its key strengths and also um what its unique selling point is of the sort of the kind of what makes the company itself special and this should be very closely aligned with um the portfolio again. So there's a unique positioning that comes out of this.
 
 
00:18:08
 
Vera Örså: So thinking about the unique positioning of the portfolio as a whole is important. If someone was looking at your company looking at your portfolio, what story does it tell um them about who you are and why you're there? So a good question to ask is you know what talking about what do you want to be when you grow up is really what do you want your portfolio or the or the key USP of your portfolio what story do you want it to say? Um and that's really the direction you should be going in. Um so if you're a biotech company um that translates into you know you have your first project. um which direction do you want to go next? You know, you can move into new diseases, um new disease pathways, drug targets, drug modalities, technology platforms and product formats. All of these are different options where you can translate sideways or or left or right, up or down to grow your portfolio and extend it. And these are strategic choices as to which directions you want to go in. Um so one of the key sort of insights that that comes from this in in thinking about this is you know based on your USP which should be centralized on what your core sort of purpose or hypothesis is is bet on what you're sure about the center of your story and hedge on everything else.
 
 
00:19:45
 
Vera Örså: This isn't a great picture, by the way, because I realize it has connotations of pure gambling, but you get the point. Um, and by the way, the only difference between investment and gambling is gambling is with where you have a an a negative expected netresent value. Investment is where you have a positive expected net present value. Um uh now hedging risk and uncertainty in portfolio management um is really about thinking about how projects relate to each other. How correlated they are. Now regardless of whether you your projects are correlated or decorrelated in other words inversely correlated or not correlated at all your your total expected net present value of your project is always the same. It doesn't matter about correlation because based on the current information you have um your your overall expected outcome will be the same and this is based on a law called the sum of expectations. Now when it comes to risk and uncertainty, this is where it does make a difference whe whether your projects are correlated or not. Because if projects are highly correlated, in other words, the success of one is automatically going to lead to the success of the other or the failure of one is uh connected one to one with the failure of another.
 
 
00:21:10
 
Vera Örså: Um you're you're just growing your risk as you're growing your expected return. Um, conversely, if you if your projects are completely decorrelated, for example, if you know that a disease must be one of three disease mechanisms, um, targeting all three is beneficial because you know if one fails, then you're actually more likely that one of the remaining two will succeed. So, there's a way to hedge your um, bets in that regard. And that's very useful because what what the impact on overall risk is quite profound. Um and again having uncorrelated projects is a nice way of uh managing risk across your portfolio. Um, now I I don't want to get too much into the math, but when you think about expected net present value, what it is is really um the probability weighted average uh MPV across all your scenarios. And you can think about mapping your scenarios um as a as a cumulative probability on the x-axis on the right here. And your value scenarios are um represented by this complex curve on the right. Now you can do a complex Monte Carlo calculation to you know to figure that out but you don't really need that when you when you think about the main drivers of your value distribution they're based on the main inflection points the go no-go decisions uh at each
 
 
00:22:42
 
Vera Örså: stage um as well as the you know the cost or the net present value of the cost of each stage and what the likelihood of ending up in different scenarios which may be fading in phase one, phase two, phase three, registration, all succeeding all the way to launch. And you can do a back of the envelope calculation and pretty much um um get your ENTPV this way. Um so here you see an expanded version of that where you can clearly see the the value of different scenarios and the probability of different scenarios um mapped in this way. And this is a useful way to to look at it and think about it as a value probability distribution. Now when you combine different projects um this depends on how they are correlated. So if you have two projects which are 100% correlated you actually don't change the shape of the curve. You have the same distribution of values but all you're doing is expanding um the scale on the y-axis. Whereas if you have uncorrelated um projects, you get the uh dark blue line.
 
 
00:23:54
 
Vera Örså: Um and here you have a lower probability uh sorry higher probability of getting a a smaller gain and a higher probability of getting a smaller loss. So you're reducing the overall spread in your value distribution. And it's even more extreme if you go for decorrelated projects where basically you take the uh value distribution of one project um invert it and add it to the value distribution of of a similar project. And here you see an even more pronounced reduction of risk. And as you add more projects in this um idea, you see that you with four projects with eight um with 64 projects, you almost flatten out completely the spread of values in your um your potential outcomes. your expected net present value keeps being additive. So you're each project adds value but by decorrelating or or making sure projects a

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