Strategic Planning In Biotech During A Pandemic Crisis

Posted March 26th, 2020 in Uncategorized | Leave a comment

In the throes of a full COVID-19 pandemic, most business leaders’ top priority is rightfully the health and safety of their employees, families, and communities. Even though business disruptions are significant and overwhelming, the primary efforts focused on both safety and the control of the spread of SARS-CoV-2, like social distancing and working remotely, are paramount.

Without diminishing the importance of those priorities, business leaders also need to think about the viability of their organizations and rapidly embrace strategic planning around the crisis. For biotech leaders, this involves strengthening efforts aimed at mitigating the negative consequences of the pandemic on the advancement of the industry’s pipeline of new medicines. Before addressing those issues, it’s important to put the economic changes and biotech’s unique capital market dependency in context.

The COVID-19 pandemic crisis has created panic in the markets: the fear index has hit its all time high, as volatility and uncertainty about the future skyrocket. Incredible gyrations in the stock market happen every few days, in both directions. Huge dislocations in the economy are happening due to the pandemic, both from the virus itself and from our efforts to “flatten the curve” around shutdowns, social distancing, and remote working. This impacts are not only with hospitality and T&E businesses (like Marriott’s 90% revenue drop in a few weeks), but also with housing (mortgage applications off significantly), energy, education, consumer goods, restaurants, and nearly every other sector.

Morgan Stanley and Goldman Sachs economists are now estimating -30% and -24% drops in the quarterly GDP in 2Q2020, more than double the largest drops in history (from the start of the Great Depression). Unemployment claims spiked and will almost certainly continue going up, bringing the US unemployment rate to 12.8%, a rate not seen in decades, according to Morgan Stanley. A massive stimulus program is coming together to supposedly cure the economy of the coronavirus pandemic. However, there’s significant uncertainty around what the post-pandemic world will look like. Will we see a rosy “V-shaped” or optimistic “U-shaped” recovery of the overall economy, or will it be a more challenging “L-shaped” slog.

But what about the biotech sector?

Biopharma stocks have weathered the storm better than many sectors, likely due to the industry’s role in the possible COVID-19 response, as well as focus on making new medicines in general; new therapies are largely “recession-proof” if they address real medical needs. The two key biotech indices, the market-weighted NASDAQ Biotech Index ($NBI) and the equal-weighted S&P Biotech Index ($XBI) are off 16% and 25%, respectively, since peaking in mid-February.  For comparison, we’ve seen much more significant “corrections” during two periods in the recent past: during 2H 2015-1Q 2016, the XBI was off 48%; in 4Q 2018, it was off 35%. This pandemic panic has lots of room to run so the markets could correct to those levels (35-50%), but I think that’s unlikely.

R&D-stage biotech firms, represented by the vast majority of private and small/mid-cap (SMid) public companies, are loss-making enterprises. They don’t have product revenues in most cases, so this pandemic won’t be affecting their sales. Consumers and their health plans don’t buy R&D-stage drugs, so changes in consumer behavior aren’t relevant in the near-term. Loss-making biotechs largely don’t have much debt financing, so tightening access to credit is not a major factor in our space.

But these emerging biotechs do have to raise funding, largely from the equity markets, to advance their R&D portfolios. In the absence of revenue multiples or other conventional financial metrics, for these loss-making biotechs, data is the ultimate currency of progress and market value. Data comes in lots of flavors: large Phase 3 outcomes, human “proof of concept” Phase 2 clinical results, safety and tolerability insights from Phase 1 studies, and preclinical experiments, among many other flavors. Fundamentally, R&D progress is measured by these data and their attractiveness; future accessibility to additional funding is often very tightly linked to favorable and advancing R&D-stage data packages.

This is where this COVID-19 crisis directly impacts biotech: the ability to get key value-creating data will affect the ability to get future funding; and, without cash, biotechs can’t get to those key data.  Importantly, even with great execution and delivery to timelines, most companies will encounter a higher cost of capital for their next financing if current conditions in the equity markets persist.  Those without data in hand will likely face real challenges.

For C-level executives and Boards of biotech companies, it all comes down to an assessment of how current cash positions link to the operational burn rates required to get to the key data inflections. It’s critical to think through how to get to data in an uncertain macro environment, and thus uncertain equity capital market, in a panic-stricken world with significant execution challenges.

R&D execution challenges

This COVID-19 pandemic is likely still in its early innings, so how prolonged the impact on biopharma business operations will last is uncertain.  But one thing is very clear: the dislocations across the global economy will almost certainly create delays in our R&D timelines, as has been described in regular columns by Adam Feuerstein at STAT News.  Here are some further examples across the R&D value chain.

Clinical development programs are particularly sensitive to the COVID disruptions. With the shutdown of the healthcare system in multiple regions of the world, and hospitals in particular, the impact on clinical trial timelines has the potential to be significant. Many sites have prohibited all elective procedures, which includes non-urgent visits and treatments for most non-life-threatening diseases. Patient screening and enrollment may be shutdown or curtailed dramatically in some geographies/sites due to travel and logistics restrictions. IRB’s at medical centers aren’t meeting to review new trial applications or approve protocol amendments. Site initiation visits are going virtual, if they are happening at all. Potential safety issues (or confounding issues) around using immune-modulating experimental agents during an infectious pandemic are now real considerations. Logistically complex trials, like those in cell therapy, are particularly difficult in this environment. All of these pose big challenges to small biotechs that were expecting to enroll patients over the next few quarters in order to obtain the key data to catalyze a future financing. But small biotechs aren’t the only ones facing this issue: Lilly recently announced delaying new trial starts and pausing enrollment in existing studies, and BMS is halting new enrollment in cell therapy studies.

Drug discovery and preclinical activities are also being pressured. Timelines in early R&D can be greatly affected by availability of key animal experiments (like IND-enabling GLP studies or critical pharmacology models) and manufacturing activities. The pandemic has created real concern around the availability of both CRO partners and vivarium access to be able to conduct these studies. When the crisis was initially hitting China in January, many feared that Chinese CRO partners there would be out for months and wreak havoc on R&D timelines; that situation has now changed. It’s the CROs in the US and Europe where the big worries are, and China appears to be coming back online. In fact, some of our discovery-stage companies have increased their efforts in China in the past week or so.  For biotechs with wet labs and in-house scientists, social distancing has certainly made productivity challenging. To protect employees, a number of larger biopharma companies have moved to “red team/blue team” models to create space and safety precautions while continuing lab operations. Fortunately, in Massachusetts, biotech R&D scientists are considered essential and exempt from “cease business operations” and “work from home” orders announced by Gov Baker. Further, for both office and lab team members, there remain significant unanswered questions around how and when to re-engage back in the workplace (e.g., what are the local or national pandemic metrics we’d need to see to ramp back up). These scientific business disruptions are undoubtedly going to affect many companies’ early stage R&D timelines.

Academic partners are critical collaborators for many early stage biotechs, and they are similarly facing productivity challenges. David Sabatini of MIT’s Whitehead Institute summed it up best via Twitter: “I’m pretty tired of hearing how we scientists are supposed to be so productive now. Anyone with kids, elderly parents, lab members to worry about, stranded masters students, etc is too stressed and busy to be thinking big thoughts.” This is a sentiment shared by academic and industry scientists alike.

Lastly, many other areas of a biotech’s business operations are also challenging. Logistics around CMC processes, ordering supplies, shipping drug substance, moving experimental reagents to other partners, etc… Space issues, never easy in challenging real estate markets like the Boston area, are also now fraught with COVID-induced complexity: building permits aren’t being acted on in many geographies, construction crews can’t engage on new lab/office space, delays to moving in mean delays to key lab equipment, leaving existing space will be hard for tenants without new space, etc… If a biotech planned to move into new space this fall after a summer buildout, those plans are likely going to be delayed – with ripple effects on R&D and organizational growth/constraints.

All of these potential sources of delay can impact the one critically important goal: getting to key catalytic data that demonstrates the value of an R&D program or portfolio.

Management teams should be doing everything in their control to optimize the execution parameters and mitigate the downside impacts on project gantt charts and timelines. Now is the time to consider “insurance” on your operating plans – adding a new clinical site or partner that can carry the execution while certain parts of the globe are offline. Putting in place the right executional “hedge” for protection of your timelines requires thinking through tradeoffs and don’t come for free.  A big part of this strategic planning process involves understanding the bookends of uncertainty and the levers we can control.

Scenario planning

The macro environment and the dislocations in the economy are not things we can control as biotech executives; the key is to understand the range of possible outcomes, handicap their likelihood, and prepare accordingly.  There are likely short, medium, and long term macro scenarios for the impact the COVID pandemic will have on biotech R&D.

As described in the matrix below (adapted for biotech from Sequoia), there’s a rosy if not overly optimistic scenario that the practical R&D delays are minimal (Scenario #1), where they may be limited to a few months. We often plan for a few months of delays in the normal course of business in R&D (timelines, amazingly, often slip out by a quarter). Scenario #1 is likely just a pleasant daydream at this point. The middle scenario (#2), and probably the most likely in my opinion, is that there are real delays that continue to impact us through the fall (“medium term”), with key R&D timelines moving out by six or more months.  The pessimistic scenario (#3) is that we face long term consequences of this pandemic on R&D timelines, leading to significant delays that add a year or more to program timelines. For the purpose of discussing the strategic planning implications, a working assumption is that the structural delays arising in these scenarios are only capable of being mitigated at the margin by operational excellence, contingency planning, backup vendor management, and the like. These are macro factors largely out of our control.

Assuming a typical loss-making R&D-stage biotech found itself entering March 2020 with roughly 18 months of cash, how should one respond to these three macro scenarios?  If the equity capital markets are closed or prohibitively expensive for raising significant additional funding, then there are several potential strategies to embark on.

If you feel strongly we’re in Scenario #1, then not fundamentally changing your R&D efforts (Plan A) may actually be the smartest long term decision: you have the cash to get you through the key data inflection points, and will be able to raise in 2021 after the pandemic and election are behind us. But under other macro scenarios, especially #3, doing nothing runs real risk of an impossible cash burn and runway situation: you’ll never get to the data you need to create value. This is the domain of recapitalizations and liquidations.

In Plan B, management teams exhibit more caution on their spending – aiming to cut burn (extend runway) to ensure that in the middle macro scenario of six month delays, you can still get to data with breathing room on the other side. In Plan C, fear takes over – and is essentially smart only if you are preparing for a “nuclear winter” with macro scenario #3. In any more modest macro setting, Plan C is an over-reaction and damages the organizational culture and its R&D prospects.

This is a Goldilocks moment for strategic planning: not too hot and not too cold. Prudent cash management that funds a biotech to the key data is the objective. Too optimistic and you risk driving off a cliff; too draconian on the cuts, and you hurt your longer term prospects.

This conclusion seems clear in the abstract for the “typical” biotech. But no biotech is typical – there are nuances around the R&D program(s), time to data, cash positions, burn rates etc… Which scenario plan (A, B, or C) makes sense for a given biotech depends on lots of company-intrinsic factors – hence the challenge to management teams and Boards.

But it’s important for biotech executives to go through a strategic dialogue with their Boards, framed by a matrix like this, and talk through the specifics of their situation and how different macro scenarios can impact their company.

Near term optionality

In the face of these macro uncertainties, buying some time – optionality – in the near term seems like the smart leadership. We’ll know better over the next couple of months whether we’re trending to macro scenarios #1-#2-#3. Right now biotechs should work to preserve strategic optionality around their path to data and future capital raises.

In the near-term, this means most biotechs should be working off a new 2020 “interim” base case operating plans that incorporate the possible macro downsides, where all key data points (e.g., development nominations, IND’s, PoC’s, Phase 3’s) could be delayed by various degrees.

Being short of key data readouts and running out of cash is a challenging place in any market, but will be particularly challenging in the near term. Companies needing to tap the equity capital markets for financing over the next 3-4 quarters could find it incredibly costly, and the cost of capital is only likely to worsen considerably if we are in the mid- to long-term macro downside scenarios.

Over the next couple months, here are five no-brainer decisions to act on in the near term:

  1. Focus on optimizing your virtual execution model.With social distancing likely to persist (to varying extents) in the months ahead, biotechs need to step up their game on remote operational excellence. This includes working closely with global partners to create new SOPs for how to engage on virtual project teams. Investing in new working models will help. Sharing of best practices by executive teams across the industry is happening organically, and these should have positive impact. This is the only way timelines don’t take a massive hit. This is where core corporate values come into place, as has been described by Surface and Synlogic executives in recent blogs.
  2. Conserve capital in the near term.To buy some optionality, reprioritizing resources to the key program(s) and pressing pause elsewhere for a couple months makes sense. This may mean slowing down non-essential hiring in the near term (e.g., a “hiring freeze”) and minimizing non-critical capital expenditures this spring. If your lab isn’t operational, perhaps delaying the planned lab hires or equipment. Unless you are certain about the magnitude of your expected delays and or macro view, doing painful reductions in force (RIFs) right now would be premature. Things may change as visibility gets better this spring, but right now buying strategic optionality is important. In a few months, significantly cutting burn, or ancillary programs, to ensure the viability of the lead program(s) may be prudent management but more visibility is needed.
  3. Shore up your balance sheet. The cost of capital is likely to go up over the next few months, so lock in any closings of equity capital in the near term. Rounds are still getting done as planned: we’ve had or will have a dozen financings close in March-April this year, and co-investors have all stepped up despite the turmoil. Teams should also consider whether venture debt or credit lines can help them get through data windows. Raising money in the summer if the macro scenarios shift towards #3 could be very challenging for loss-making biotech companies. Also worth considering if SBIR and other non-dilutive sources of funding make sense, as those are long lead time items. In addition, the details of the current pandemic stimulus plan aren’t clear, but this could involve financial support for the sector if 2009 is any guide, where $10B was earmarked for biomedical research.
  4. Seek Pharma partners openly and actively.The reality is Pharma has cash flow and huge warchests, which is likely going to continue even in this pandemic crisis. Beyond just cash, Pharma can bring stability to programs and reduce the entropy associated with operating in a pandemic. Finding good long-term partners could be especially valuable for platform companies with broader portfolios; since the equity markets may be less accommodating, pharma partners may help advance non-lead programs. Regional deals for China or Asian rights may be worth pursuing as a way to strengthen balance sheets. Option deals, recently out of vogue, may be of interest again to hedge future uncertainty. 2020 is likely the time to get good deals done, and to not let the perfect deal be the enemy of the good.  I’d expect to see partnering announcements pick up in the latter half of the year.
  5. Remember Eisenhower: “Plans are worthless, but planning is everything”. Right now we are surrounded by uncertainty and volatility, so it’s far more challenging than “normal” to fix a strategy in stone. Continually revisiting our assumptions as we learn more in this unfolding pandemic is critical for modifying our strategic and operating plans: adaptability will be the hallmark of winning companies. It’s critical to think through the various contingencies if Scenario #1, #2, or #3 – or another variant of them – emerges. In addition, it’s valuable to understand how fundraising windows play into the “degrees of freedom” you have for decision-making; wait too long for certain decisions and you may lose the optionality, or vice versa – some choices are mutually exclusive with others.  All this comes out in thorough planning process. Engage your Board and your key shareholders in your various battle scenarios.

During a once-in-a-decade crisis like COVID-19, biotech executives need to step up their strategic game and integrate various macro scenarios into their planning. We won’t have great visibility for a few months on how the COVID pandemic disruption will play out for biotech’s R&D programs, but buying optionality in the near-term and pushing a candid assessment of strategic plans is critical.

Hopefully, with the right strategic discussions and decision-making in the near term, the biotech sector can avoid being paralyzed by this market dislocation and collectively advance our innovative R&D pipeline through to their next inflection points. Patients need these new medicines regardless of a viral pandemic.

 

 

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BioPharma M&A Drives More Efficient Resource Allocation

Posted March 2nd, 2020 in Biotech financing, Capital efficiency, Capital markets, Exits IPOs M&As, External R&D, Pharma industry, R&D Productivity | Leave a comment

M&A is an omnipresent reality in the biopharma industry, from Big Pharma mega-mergers to smaller acquisitions of emerging startups.

We’ve recently witnessed several large M&A transactions get closed or announced, including BMS-Celgene, Takeda-Shire, and AbbVie-Allergan; according to BMO Capital Markets data, there was nearly $260B in M&A deal activity in 2019. Over the past eight years, we’ve seen over $1 trillion in M&A deal values in aggregate.

For R&D-stage M&A events, more relevant to the loss-making biotech universe, we saw $45B in 2019, similar to the boom years of 2015 and 2018. This year is off to a good start with Gilead’s $4.9B acquisition of Forty Seven Inc announced today, among others.

In short, we’ve seen a huge amount of overall deal activity in the biopharma space in recent years.

While high profile biotech acquisitions are often celebrated as wins, rarely are the bigger mergers viewed favorably. Pundits and policymakers often claim these larger M&A deals do a myriad of bad things: destroy value, distract R&D groups, consolidate market power, take out emerging competitors, and negatively impact drug pricing. The recent dissenting opinions on the BMS-Celgene merge from two FTC commissioners highlighted this perspective, as both were against approving the deal because of the possible negative competitive impact.

Most academic analyses of big mergers focus on the impact to the merged company itself: what happens to R&D spend, what happens to employees, etc… Often these analyses conclude the deals were “bad for innovation” (here) by reducing the combined R&D activity at the merged entity (or even competitor firms).

What these analyses fail to consider is the overall ecosystem benefits of M&A activity – a crucially important aspect that needs to be better appreciated by politicians and policymakers in Washington: fundamentally, large and small M&A deals, on the whole, help catalyze a more efficient allocation of scarce resources across the sector, especially over the longer term.

Before diving into why that’s the case, some additional background is warranted.

First, relative to many R&D-intensive industries, Pharma is incredibly fragmented. No single player has more than 10% market share in most broad market categories, including across sales metrics and R&D activity metrics. Further, we have hundreds of thousands of researchers on big and small R&D teams chasing the scores of new and established targets and developing new drugs against them. Failure rates are extraordinarily high, as we all know – and the cost and time to bring a drug forward remain significant. Once on the market, we also have a huge number of sales representatives, or specialty medical affairs folks, out in the clinical community trying to convince physicians of a drug’s merits. All of this leads to massive redundancy and hyper-competition on the highest impact approaches. It’s easy to argue there is frequently a temporal misallocation of talent, science, and capital resources at the industry level (see this blog’s commentary on oncology’s concentration from 2012 and 2016).

Second, there’s also a massive difference in the “cost of capital” across different players in the sector. This means there’s a huge difference in the ability of players to fund the long journey from idea to full market commercialization. The larger profitable biopharma companies have a cost of capital near zero – they have significant cash flows, large balance sheets, and can raise low interest rate debt at will. Contrast this to the loss-making biotech world, where access to new capital (funding) is always an issue. Even in the latter group, there’s a huge range in the cost of capital from startups (very high) to pre-profit “small and mid cap” biotech companies. As a sector, allocating our capital (and, by extension, our talent and science resources) efficiently is critically important if we are to keep investors involved the space versus moving their capital to other sectors.

Lastly, the steady rise of emerging biotech over the past few decades as a powerful force for innovation is well accepted: more drugs are being discovered by smaller firms than ever before, as evidenced by the increasing proportion of active INDs and new drug approvals (NDAs) attributed to smaller firms. The biotech phenomenon of the past decade, with stock market indices up ~500% since 2010, has been heralded as the “golden age” of biology and medicine. While there are many contributors to this biotech success story, one of the unsung heroes has been the steady march of M&A deals in our ecosystem as a tool for efficiently (re)deploying resources.

In short, M&A has helped address some of our ecosystem’s redundant and bureaucratic inefficiencies, like those highlighted above, by helping the sector better allocate the scarce value-creating resources of talent, science, and capital over the long term.

Talent

Every big and small merger contributes to the fluidity of the biopharma talent market.

In the five years between 2009-2013, according to the Wall Street Journal, Big Pharma companies shed at least 156,000 American jobs. Many of these were in R&D, and many of those individuals moved into emerging biotech firms, CRO partners, or other players in the biopharma ecosystem. The disruptive impact of M&A integration on a merged company’s organization is almost certainly real, but as a sector it should be offset against the benefits of bringing catalytic new additions into the talent pool – either into younger biotech firms or cross-fertilizing with other Pharma organizations.

As I’ve written before, talent acquisition from Pharma is the lifeblood of startup biotech. Most of the executive teams around the industry spent some time in large Pharma companies. By my quick estimate, more than 90% of our three dozen CEOs spent some time in their careers in Big Biopharma companies. These experiences are important, and contribute to the grey hair in the C-suite that enables better judgement.

Thinking of the Boston, the diaspora of biopharma executives from acquired firms has been essential to the success of the cluster; for example, when Genzyme, Millennium, and Wyeth/Genetics Institute were acquired by Sanofi, Takeda, and Pfizer, respectively, it prompted a significant migration of talent about a decade ago. We’re seeing that now with former Shire and Celgene teams in the Boston area. The same is true in other geographic clusters, with talent movements from acquisitions of Genentech, Immunex, IDEC, OSI, Tularik, and many others over the past two decades.

Of course, talent movements occur without mega-mergers and big M&A events as part of ‘normal’ talent turnover. But M&A creates temporary but significant dislocations that certainly enhance the local volume and overall fluidity of the talent market.

Smaller M&A deals, which are much more frequent, are also crucial for these talent flows – contributing to the recycling of serial entrepreneurs to seed new teams and startups. Many of our current portfolio executives came from prior M&A exits at Padlock, Nimbus, Stromedix, Arteaus, etc…

In short, by liberating talent to find new opportunities, large and small M&A alike help create liquidity in the talent market. This liquidity better matches prospective candidates’ skills with companies’ capability needs – which over the long run creates a more efficient deployment of talent across the ecosystem.

Science

M&A also has a dramatic impact on the scientific portfolios of the post-merger entities. It certainly changes the critical filters for evaluating programs, and almost always alters R&D capital allocation decisions. As described well by others, two simple ways to improve R&D productivity are to (a) start projects based on better science and (b) improve decision-making around what programs to allocate capital to. M&A can and often does help with both of these areas.

In the case of mega-mergers, the integration of two predecessor companies brings a new lens to program and portfolio prioritization. Fresh eyes with less familiarity or confirmation bias can often lead to better (or at least different) decision-making about what science to fund vs kill, and what projects to start. New reviews also deprioritize drug programs that are either below the bar in their opinion, or are in disease areas outside of the scope of the newly merged entity. Some of these ‘deprioritized’ assets remind me of the phrase that “one man’s trash is another man’s treasure”: differences of opinion on the merits of different programs is part of the science shuffle that occurs after mergers.

Thankfully, with the rise of external R&D models over the past two decades, these potentially interesting or off-strategy assets are often spun-out to other Pharma companies or emerging biotech portfolios. Some will even have new startups nucleated around them. The number of biotech companies with ex-Pharma assets as their lead programs is strikingly large, and these programs are often liberated through post-merger scientific portfolio reviews.

Again, like talent, there’s a natural cadence of spinning out assets during ‘normal’ periods of portfolio assessment that gets significantly amped up by M&A dislocations. It’s fair to say that lots of VCs and entrepreneurs are hungrily pouring over (or awaiting lists of) out-licensing opportunities from Takeda, AbbVie, and BMS following their recent acquisitions.

Acquisitions of smaller biotech firms can also help deploy science more effectively. Most startups are constrained by their capital base, so doing broad and expansive Phase 2 or 3 campaigns is incredibly challenging. Most startups don’t run half a dozen parallel Phase 2s in different indications with a single program; cash-rich Pharma does this all the time. So biotech M&A can put exciting assets into larger organizations who are much more resource-enabled for bringing them to the broadest patient population around the globe in the fastest possible time.

These are a few perspectives of how M&A can lead to a more efficient advancement of scientific substrate at the industry level.

But beyond just bringing assets into new organizations, these M&A transactions put science into the hands of new organizational champions – those protagonists who are deeply committed to bringing the scientific programs forward to patients and the market, like John Hood with fedratinib. Without passionate champions, projects don’t make it through R&D gauntlet and into new approved drugs, at either small or large companies. The combination of a more fluid talent and science marketplace helps advance these new potential drug candidates by more efficiently aligning them with new passionate leaders.

Capital 

M&A events liberate a lot of investor capital that recycles back into the ecosystem.

The scale of this recycling from M&A is mind-boggling. Geoffrey Porges at Leerink estimated in July 2019 that nearly ~$180B in cash was returned to investors via M&A over the prior 12 months – in comparison to less than $30B in equity financings (IPOs, Follow-ons) over that period. Porges’ conclusion is one that I also share: “…the magnitude of these liquidity events could explain the surprising durability of the capital markets cycle in the sector.” When cross-sector fund flows into biotech have been stagnant (as we’ve seen with the puts and takes of fund flows in recent years), one of the major buyers in the equity capital markets are healthcare funds that are redeploying cash from portfolio M&A events into new purchases of equity issued by biotech companies.

The recycling of capital from these M&A events has several effects worth calling out specifically.

First, M&A sends cash back to a large number of institutional public investors, which of course increases the availability of funding for cash-burning companies. This makes it easier for later stage biotechs to issue equity in the public markets, as well as in pre-public crossover rounds.

Second, M&A sends “realized returns” back to the Limited Partners of VC funds, helping the latter report better IRRs and investment multiples, which over longer cycle times increases the interest of LP’s in the space. Historically the ugly stepchild of Tech venture capital, Biotech has never seen LP interest in the sector as strong as there is today. This means raising biotech venture funds is easier, and this increases the supply of venture capital funding available for new startups and younger private biotechs. In line with that, venture capital funding into private biotechs has risen 3-fold in the past eight years, to a run rate of $20B+ per year.

Both of these effects work to dramatically reduce the cost of capital for innovative biotech companies across the spectrum – from new startups to SMid-cap pre-launch biotechs.

By freeing up capital, often from illiquid private or thinly traded public stocks, M&A enables investors with the opportunity to reassess where they’d like to deploy their capital – thus improving the liquidity and efficiency of capital allocation across the sector. Innovative projects are able to attract more capital in this environment, and are afforded with a lower cost of capital in the process.

Large M&A events in biopharma are frequently viewed with negativity, by both academic critics and government policymakers. These transactions certainly can create significant disruptions for the merged entity, with potentially negative impacts on that firm’s R&D productivity.

But the beneficial impact of M&A on the overall biopharma ecosystem is profound and should be better appreciated by those involved in policy: in short, by improving the efficiency of allocating the scarce resources of talent, science, and capital across the sector, M&A drives huge benefits – and much of biotech’s current success in advancing innovation stems from these long term positive impacts.

 

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