Category Archives: R&D

Sanofi, Evotec in major infectious disease R&D transfer and license deal

Wax Selection – Leaders in Pharma, Biotech & MedTech Recruitment

Big Pharma Sanofi and German CRO-biotech drug discovery hybrid Evotec are penning a deal that will see Sanofi license out a host of infectious disease assets to the biotech, with 100 staffers also moving into its R&D engine.

Sanofi is paying a one-time, upfront fee of €60 million ($74 million) to Evotec, a small sum, but one backed up with a promise to “provide significant further long-term funding to ensure support and progression of the portfolio,” although exact financial details were not shared.

The deal drills down like this: Sanofi will license most of its infectious disease (ID) research and early-stage portfolio (around 10 assets all-told) and move this unit, with around Sanofi 100 staffers alongside it, into Evotec (although this does not include the French pharma’s vaccine R&D unit).

Evotec, which does its own research and also relies heavily on external collaborations with biopharmas and academic biomedical research, will run this “open innovation platform” near Lyon, France, where Sanofi Pasteur is HQ’d.

Sanofi holds on to certain option rights on the development, manufacturing, and commercialization of anti-infective products and will “continue to be involved in infectious disease through its vaccines research and development and its global health programs,” it says in a statement.

The focus of the Evotec drug discovery will be on “new mode-of-action antimicrobials,” the pair say.

Werner Lanthaler, Ph.D., CEO of Evotec, said: “Since the acquisition of Euprotec (UK) in 2014, Evotec has had a significant strategic interest and demonstrated expertise in infectious diseases research, with an ambition to grow and become the drug discovery and development leader in this space together with its partners.

“We are pleased to be working and expanding our strategic relationship with Sanofi, which has a long history in providing novel anti-infective agents to markets globally. Finding a way to motivate more public funding and academic initiatives for the progress of novel anti-infectives on Evotec’s platform will be a key success factor for this initiative.”

The deal is still being talked over, but should be done in the coming months.

Evotec already has a series of deals with the likes of Eli Lilly, Tesaro, Oxford University, and even has its own spin-out in the form of Topas Therapeutics.

Elias Zerhouni, M.D., president of global R&D for Sanofi, adds: “Research in the field of anti-infectives is an area where building critical mass through partnering is particularly important. This new French-based open innovation center will benefit from the high-quality science ecosystem. Evotec is a trusted partner in drug discovery and has the ambition and capacity to become a real leader in the fight against infectious diseases.”

This also comes as Sanofi continues to retool its R&D, getting back into cancer as well as blood disorders via its $11.6 billion deal for Biogen spin-out Bioverativ.


The third wave of AI in pharma R&D

Wax Selection – Leaders in Pharma, Biotech & MedTech Recruitment

The capabilities of artificial intelligence are advancing and its ‘third wave’ offers the ability to analyse enormous sets of data, identify patterns, and generate algorithms to explain them, to the benefit of researchers.

The digital revolution vastly accelerated the research, development, and production of new drugs. Digital technology has augmented the natural capabilities of researchers and scientists in a variety of ways. Now, artificial intelligence (AI) is poised to take this augmentation to the next level.

One of the most significant ways in which AI technology augments human capacity – particularly in an R&D context – is by automating repetitive, lower-level cognitive functions that once had to be carried out manually. This liberates drug researchers to focus on higher-level thinking. This advantage was identified early in the development of AI technology by J C R Licklider, who wrote back in 1960 in Man-Computer Symbiosis:

“About 85% of my ‘thinking’ time was spent getting into a position to think, to make a decision, to learn something I needed to know. Much more time went into finding or obtaining information than into digesting it.”… “Several hours of calculating were required to get the data into comparable form. When they were in comparable form, it took only a few seconds to determine what I needed to know.”

A related idea was expressed by Herbert A Simon with the concept of ‘bounded rationality. He wrote that humans’ decision making can be optimised when they are provided with a limited quantity of relevant, focused information and sufficient time to process it.

With the advent of contemporary AI technologies, the bounds of human rationality have been expanded. AI provides drug researchers with a greater breadth and depth of data that is simultaneously more focused and relevant than the data sets of the past, enabling researchers to optimise their decision-making capacities.

The continued advancement of AI will augment humans’ power of critical thinking in three key areas that are relevant to the medical and pharmaceutical industries: computing advanced mathematical problems, analyzing complex statistics, and generating novel hypotheses. These areas correspond to the ‘three waves’ of AI development throughout the 20th and 21st centuries.

The first and second waves

The first wave of AI development brought us ‘knowledge engineering’ optimisation programs, which solved real-world problems efficiently.

While applications specific to the pharmaceutical industry were scarce, the broader medical field benefits from first-wave AI technologies every day. Take the Framingham Risk Score Calculator, which utilises AI to predict the heart disease risk of any patient.

Machine learning programs were brought along by the second wave of AI. These solve complex pattern recognition problems using statistical analysis. Unlike their first-wave predecessors, second-wave AI programs perceive and learn – often as well as humans do.

Clinical decision support systems use second-wave pattern-recognition programs to analyse and evaluate medical test results. Similar machine-learning programs are beginning to be used by leading pharma firms in a variety of research and development contexts to predict drug effectiveness, to discover new compounds with pharmaceutical qualities, and to develop new combinations of existing drugs.

Second-wave AI is powerful, but it demands well-organised, consistently-coded, and complete data sets in order to accurately conduct its analyses. This limitation is now being overcome by the third wave of AI.

The third wave

We have now entered the third wave of AI development. Third-wave AI programs have the capacity to analyse enormous sets of data, identify patterns, and generate algorithms to explain them. These programs normalise the context of disparate data points and generate original, novel hypotheses at a faster rate and with greater accuracy than human researchers can.

Only in this third wave have AI programs reached a sufficiently advanced state to effectively analyse the vast and complex web of unstructured biological data. Until recently, biological data had to be manually cleaned and organised through extensive and costly human effort. Now, AI programs use a combination of machine learning, natural language processing, and text analytics to analyse unstructured data in real-time.

Through context normalisation, third-wave AI technology dramatically increases the quantity of data that can be analysed in the course of the drug discovery and testing process. Furthermore, it enables the simultaneous generation and testing of new hypotheses at a rate that would be impossible without such immense computing power.

Aided by this technology, drug researchers can arrive at a higher quantity of more accurate hypotheses and can test these hypotheses with unprecedented speed. The result is a significantly faster, and less expensive, discovery process, with lower risk and more effective results. Firms such as Pfizer and Johnson & Johnson are employing such methods to great effect.

Given that R&D consumes as much as 20% of pharma firms’ revenues, and that the total price of developing a new drug has ballooned by 250% in the last 30 years, it’s not surprising that firms are eager to embrace third-wave AI as a means of accelerating drug development.


How can pharma navigate the complex marketing landscape?

Wax Selection – Leaders in Pharma, Biotech & MedTech Recruitment

The first chapter of pharma’s commercial evolution takes us from the insatiable sales-drive of the 1980s to the present, highly complex marketing landscape.

It is easy to forget that our competitive industry still has 80-90% gross margins and, as a consequence, its traditional commercial model is driven by sales growth, rather than worrying about costs.

Under most circumstances, incremental sales drive incremental profit. Within the affiliates this is obvious, and country managers have often resisted attempts by corporate counterparts to take a centralised approach to sales and marketing, claiming their country’s commercial ecosystem is unique and not amenable to meddling.

Of course, the modern pharma company will also have to conduct market access, medical education and phase IV studies within its affiliates, but the reality is that most affiliate activity is focused on sales. For large pharma companies the sales and marketing budget usually beats R&D budgets by 1.7 times, and this is becoming increasingly difficult to justify.

Rise of primary care dominance

Throughout the 1980s and 90s the focus on sales-driven growth led to the evolution of some very different ways of working within primary care, from co-promotion and co-marketing with embedded local players, to the ‘petal’ system of multiple salesforces detailing overlapping product ranges.

The purpose of these techniques, together with employment of contract sales teams, was a sort of ‘shock and awe’ strategy which swamped the physician with frequent visits about particular products. The competitive response was usually swift and commensurate, resulting in a commercial arms race between players within a hotly contested therapeutic area.

This was known as the ‘share of voice’ model, and when applied to large primary care categories, it drove top line growth so successfully that governments and institutional payers were forced to find a response to escalating drug bills around the world.

Backlash from health technology

This response varied from country to country, but has taken two main forms; the Health Technology Assessment response and the consolidated payer response. Throughout the 1990s and 2000s, in the UK (NICE), much of Europe, Australia and parts of Asia, there has been systematic developing of a process that assesses whether a product represents value for society.

Much of the health economics work is shared among countries, and pricing comparisons made between the same product in different countries are routine. The benchmarks for the monetary value of a healthy human being are the subject of debate, but are necessary to make budgetary choices in a system without unlimited resources.

The consolidated payer model, operating in the US through pharmacy benefit managers such as Express Scripts, relies on large payers exerting pressure on manufacturers for rebates, with some undifferentiated product portfolios having to rebate as much as 50% of their gross price.

The impact of health technology assessments can be seen today, manifesting itself in pricing pressure, therapeutic substitution, a diminution of decision-making by physicians and a conscious shift towards products with a confirmed medical need. A decline in R&D productivity, however, has not made this process easy.

Dead end: Primary care hits a wall

Many commentators blame the decline in R&D productivity for the steep fall in product approvals through the 2000s but, in reality, there have been several forces at work.

The rise in genomics, together with high-speed screening techniques, led to a belief that chemical libraries could be screened against unprecedented targets and that optimised drug candidates would flood through the discovery phase into phase I trials.

The sharp product rise in the early clinical phases then came to a shuddering halt during phase II ‘proof of concept’ studies, when large numbers of clinical failures unveiled the reality – there is no short cut to understanding disease biology.

As research cul de sacs were explored, a squeeze on primary care products began in the form of price pressure from above and greater safety demands from below. As a consequence, and aided by the rise in technology, a rapid increase in the proportion of newly-approved, biological in origin drugs commenced.

Monoclonal antibodies, vaccines, enzyme replacement therapy and other therapeutic peptides, aided by insatiable demand for insulin, developed strong sales and completely changed the nature of commercial interfacing with physicians.

Biologicals change the commercial dynamic

The pressure on primary care products, together with the impact of the patent cliff in 2012/13, have combined to drive sales of primary care products into stagnation. Much of industry downsizing, particularly within commercial operations, has been in response to this.

Perhaps most merger and acquisition activity within pharma also has its origins in this relentless pressure on primary care sales and the need to reload the pipeline quickly with biologicals and specialties.

The success of biologicals and other specialties, such as oral cancer drugs, in terms of both approval and sales, has required the industry to change its commercial emphasis. The huge traditional focus on primary care or family doctors has changed to specialists, and their support workers within a secondary care or hospital environment.

The increased complexity of the specialty sell, sometimes involving multiple decision-makers, formulary approval, health economic arguments, companion diagnostics and performance-related reimbursement, has required a much smaller, but more skilled group of people to interface with the healthcare network.

Many companies have yet to find the necessary mix of skills within their workforce and are still working under the old assumptions that spending on promotional activities can remain as high as it used to be under traditional models. They do so at their peril. Check out Part 2in the next issue, as promotional resources and modern data come under intense scrutiny.


AZ tops annual R&D spend in UK, Roche is greatest pharma spender worldwide

Wax Selection – Leaders in Pharma, Biotech & MedTech Recruitment

New findings of a report by PwC have revealed the biggest spenders in R&D worldwide as global spending hits $700 billion, with Roche coming out on top within the pharmaceutical industry with a total expenditure of $11.4 billion in 2017, a 14% increase on the previous year which brought in a huge 21.9% of its total income.

Even with these impressive figures, the company made it only to seventh on the global list, beaten by the likes of Samsung, Intel and Alphabet, while Amazon topped the chart with a massive $16.1 billion injected into research – a 28% increase over 2016 and responsible for almost 12% of the firm’s total revenue.

Elsewhere in the global top ten were MSD with $10.1 billion which drew around a quarter of the firm’s income after an increase in investment of 51% over 2016 – far and away the most in the top 20 – and Novartis, which made $9.6 billion with a tiny 0.6% increase in spending.

In the UK, the pharmaceutical industry was far more dominant when it came to R&D spend, with AstraZeneca topping the list with $5.9 billion, followed by GlaxoSmithKline with $4.5 billion – the only pharma companies to make the top ten in the region.

The report also highlights the threat that protectionism economic policy poses to the UK and the US, with 52% of 562 surveyed R&D leaders believing that the Trump Administration’s import and export approaches and the uncertainty of Brexit will have a moderate or significant impact on R&D efforts in the future.

John Potter, a partner in PwC’s consulting arm, said: “To deliver innovation, many of world’s largest companies rely on shifting talent, money, and ideas across borders. If policies in the major global economic powers start to focus more inwardly, however, this would cast uncertainty over companies’ innovation plans and their current models would need to evolve.”