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- Herausgeber: ibidem
- Kategorie: Fachliteratur
- Serie: Schriftenreihe Masterstudiengang Consumer Health Care
- Sprache: Englisch
Raising costs, ever-increasing regulatory hurdles, and mounting difficulties in finding the next blockbuster drug are just a few of the challenges Big Pharma currently has to face for its research and development process, the heart of its risky business. Big Data claims to be full of insights that Big Pharma need to find a way of harvesting, which could lead to new compounds. Academics, Big Data start-ups, and pharmaceutical companies have focused their research efforts on analytic tools and data technologies to store, collect, analyse, and extract these insights from massive data sets. However, the key question is whether the Big Data hype really does have the claimed accelerating effect on the complex research and development process or if it actually creates another hurdle for Big Pharma innovation. Malena Johannes' timely book sheds light on this question by examining the top 5 pharmaceutical companies and provides an overview on the status quo of Big Data applications within the pharmaceutical industry.
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Seitenzahl: 146
Veröffentlichungsjahr: 2016
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ibidem-Verlag, Stuttgart
Table of Contents
Abbreviations
EU
European Union
FDA
Food and Drug Administration
HTA
Health Technology Assessment
HDFS
The Hadoop Distributed File System
HQL
HiveQuery Language
NGS
Next Generation Sequencing
NME
New Molecular Entity
NoSQL
Non-RelationalStructure Query Language
PhRMA
The Pharmaceutical Research and Manufacturers of America
R&D
Research and Development
RWD
Real World Data
RWE
Real World Evidence
SQL
StructureQuery Language
Summary
Largeamounts of digital data, from geographic location to data search history,are generated automaticallywith any online activity. Theincreasing number of people, devices, and sensors connected by digital networks further expands this body of data. Theability to store trillions of bytes of information and the constant research into analytics tools to extract value from the unstructured data flood, collectively known as ‘Big Data’, has the potential to positively support businesses in many industry sectors including healthcare.
In the last two decades, the pharmaceutical industry has seen a steadily decline in research and development (R&D) productivity caused by increasing costs, while the number of new pharmaceutical compounds obtaining market authorization has been stagnant, driven by ever-increasing regulatory hurdles and mounting difficulty in finding the next blockbuster drug (either in a new disease area or a far superior product to what is currently in the market). The pharmaceutical industry has looked at many ways to address the innovation gap, starting with increased R&D spending, followed by major consolidations, in-licensing, acquisitions and R&D re-organization – but to no avail. Big Data experts claim that the pharmaceutical industry needs to take better advantage of today´s data phenomenon and look into ways to connect disparate data from external sources in the healthcare world in order to reinvigorate the R&D engine.
In fact, pharmaceutical companies have started to embrace Big Data for their R&D process, but the big question remains whether this hype will help toaccele-rate drug innovations. This studyexamines this question by conducting an online research looking at the top five pharmaceuticalcompanies (‘Big Pharma’) by re-venue in 2014 – Novartis, Pfizer, Sanofi, Roche and Merck & Co. The results demonstrate that all of the examined companies have started to implement Big Data for R&D, in particular in the field of oncology, to help identify and validate new drug targets and improve patient stratification. Though it is too early to draw definite conclusions of the impact that Big Data can have for the R&D engine, there are signs that Big Data can contribute to the successful completion of clinical trials. Big Pharma’s utilization of Big Data is still in the early stages and the industry will need to continue investigating how to best implement and use Big Data for its business needs and research focus to extract the most value out of the data explosion.
1. Introduction
“We have discovered the cure for cancer, we just can´t find it.”[1]
(Research and Development Executive, Global Pharmaceutical Company)
Evolutions in technology, increasing digitalization,and an era of open information- there are many reasons that have led to the massive, hard-to-handle amounts of unstructured data. Big Data has become the buzzword of the decade. Industry leaders have started to embrace the data phenomenonand aim tounlockthe claimed business potential.Ironically, the pharmaceutical industry is one of the industries that late joined the Big Data hype, although no other industry is and has always been more dependent on data. Any new drug that a pharmaceutical company brings to market has to demonstrate an extensive set of clinical trial data to prove a positive benefit-risk profile in order to seek marketing authorization. Furthermore, data determines any business decision within the research and development (R&D) process, the heart of the risky business a pharmaceutical company has to face. The development of a new drug is an investment of around US$2 billion and takes on average 14 years.[2]Any failure is a huge financial loss, and in fact, failures are not rare. Out of over 200 pipeline projects per company per year[3](see appendix 1 for more details), only 0.6 new pharmaceutical compounds make it to the market[4]. The Big Data buzz claims to have the potential to reduce costs and time by improving patients’ outcomes at the same time. Moreover, Big Data claims to open new ways of research pathways resulting in, for instance, personalized cancer drugs that would never have made it to the market a decade ago as clinical trials were not designed to meet niche patients’ needs and as such, would not have met the targeted clinical endpoints.
Big Data claims to be full of insights that Big Pharma need to find a way of harvesting, which could lead to new compounds. Academics, Big Data start-ups and pharmaceutical companies have focused their research efforts on analytic tools and data technologies to store, collect, analyse and extract these insights from massive data sets. However, the key question is whether the Big Data hype really does have the claimed revolutionary effect on the complex R&D process or if itactuallycreates another hurdle for Big Pharma innovation? The goal of this researchis to shed light on this question.
2. Objectives and scope
The objective of this studyis to examine whether and how the top 5 pharmaceutical companies are applying Big Data for their R&D processes as well as to whether Big Data initiatives have proven to increase R&D efficiency. Based on the pharma revenue in 2014, the latest figures show that Novartis, Pfizer, Sanofi, Roche and Merck & Co. are currently the five leading pharmaceutical companies and have thus been selected as the subjects of this research.
Figure 1: Top 5 Global Pharmaceutical Companies based on Pharma Revenue in 2014
Source: Statista (2015)
Thereby, the following key questions will beexamined:
·Which of the top 5global pharmaceutical companies areactive in the field of Big Dataand R&D?
·What are theareas within the innovation processof anew pharmaceutical compoundthat pharmaceutical companies are mostinterested toutilizeBig Datatoinformstrategies?
·If the information is available: How much do Big Pharma invest into Big Data strategiesfor R&Dfrom a financial and resourcing perspective?
·Have the selected pharmaceutical companies initiated collaborations with other pharmaceutical, biotech or IT companies/research institutes or other stakeholders within the healthcare sectorconcerning this matter?
·Is Big Pharma still in the experimental stage or are there already Best Practice Cases available on successful Big Data activities for R&D?
·Have Big Data initiatives proven to demonstrate a higher success rate for the overall R&D process than traditional R&D approaches?
3. The innovation gap in R&D for the pharmaceutical industry
3.1 Challenges of the innovation process
Innovation in the pharmaceutical sectoris a highly complex, lengthy and risky process. No other industry issignificantly more linked to science and more regulated.
The traditional innovation process is divided into preclinical research including drug discovery and preclinical testing, clinical development (phase I-III) and a regulatory review and finally, the launch phase.[5]
Figure2:The phases of clinical development, registration and launch & sales
Source: Own illustration based on Gassmann (2015), p.64-65
While the process of developing and bringing one new compound to the market takes on average 14 years, another specific characteristic is that pharmaceutical R&D also faces a low probability of success. Only one of more than 100,000 compounds that have been screened in discovery research make it to the market – even from the discovery stage, the number is whittled down to one in 10 by the pre-clinical research phase. In fact, the probability of discovering, developing and registering a new molecular entity has been estimated to be only around 4%, which makes it a risky and cost-intense business.[6]
Figure 3:The traditional R&D process and principle timelinesof a new compound
Source:Schuhmacher(2015), p.46
According to Ding et al. the complexity of the innovation processin the pharmaceutical industrycan be described by the following three characteristics:Live or die, large in size, and finite lifespan.
Live or dieis the pragmatic expression for the risky business that pharmaceutical companies have to face.A pharmaceutical company can only survive if its R&D efforts pay off. In other words, an empty pipeline, failures of drug compounds during the clinical phase resulting in the absence of drug launches puts a pharmaceutical company at risk.
Large in sizerefers to the fact that each new drug tends to generate a large amount of revenue for a firm. A successful so-called blockbuster product that generates at least US$ 1 billion per year in revenue can outweigh the costs for failed research; in turn, a firm´s loss of income from a drug compound is usually accompanied by a significant drop in the overall performance and profit. Hence, pharmaceutical companies face the ongoing challenge of delivering consistent results and ensuring stable and successful innovation.
Finite lifespanmeansthe limited time that a new innovative drug willbe valuableandbring in significantrevenue to “pay back” the R&D costs. The standard lifespanof a drugis defined by the patent validity.[7]As soon as the drug´s patent expires, generics will enter the marketand take over a high segment of market share, leading to a significantly revenue decrease of up to 90%.[8]To put numbers into perspective, projected revenues of all new molecular entities between 2012-2016 are expected to be US$58 billion whereas losses by patent expirations are forecasted to be US$123 billion.[9]In addition, it is worth noting that only 3 out of 10 drugs generate revenue that meet or exceed average R&D costs.[10]
Therefore, a pharmaceutical company has to consider and balance the following four key dimensions: cost, uncertainty, return and time.
Cost:
The costs for the development ofa new drug areimmense. Excluding any other factors and assuming the development for a drug takes 14 years, today´s total costs for R&D per compound is US$1.8 billion.12An increase in the interest rate and any prolongation of the R&D timeline has a negative impact on costs. Further, costs of R&D have risen rapidly over the last decades and have doubled every 8.5 years since 195012, driven by larger and more complex clinical studies and expensive new enabling technologies. Before 1990s, the R&D costs were less than US$250 million; in 2000, the costs rose to US$803 million and by 2005 surpassed the US $ 1 billion mark (approximately US$1.3 billion[11]). Since then, costs have steadily increased and are expected to soon hit US$2 billion. The clinical development phases, from Phase I to submission, account for 63% of these total R&D costs.[12]Consequently, the costs of developing a new compound have an impact on the innovation decision and hence limit the number of new drug projects that a firm can support at a given time.[13]
Uncertainty:
Uncertainty is related to the low rate of probability of successfora new molecular entityto cometo the market.Each phase of the innovation process entails the risk that a drug can fail for various reasons. A review of theFDAin 2012 demon-stratedthat most failures at Phase II and Phase III resulted from insufficient efficacy of the drug demonstrated (56%), followed by safety concerns (28%).Dif-ferencesin attrition rates may depend on the drug class, the therapeutic area, the type of disease, the source of the drug candidate (self-originated drugs vs. in-licensed drugs), and the size of the company. For example, central nervous system (CNS) drug candidates have a higher probability of failure in later stage clinical trialsdue tothe lack of predictive animal models in the discovery research and the pre-clinical testing phase.[14]
Return (of investment):
Returnof investmentis closely associated with uncertainty.Key for sustainability is the balance of uncertainty with potential return. As mentioned before,each new drug has the potential to create substantial value for the company. As such, a pharmaceutical company must select innovation projects that can potentially provide large-scale return to at least make up for future lost income due to patent expirations of existing blockbuster drug or failures during the R&D process. In turn and conditional upon this, the executive board of a pharmaceutical company must also assess how much uncertainty it is willing to bear to target an even larger return. First-in-class innovations result in higher revenue, but have higher attrition rates. Me-too drugs[15]have a lower potential of large-scale revenue, but the de-velopmentprocess is less risky and the probability rate of success is significantly higher.
Time:
Timeis not only measured as how long it takes to develop and bring a drug to market, but also includes the limited length of patent protection of a new mole-cularentity. The majority of the income of a pharmaceutical company comes from drugs with patent protection so it is critical for a firm to plan ahead and initiate new clinical trial programmes to ensure new drug compounds are available for launch when patents of existing blockbusters expire to replace the expected loss of revenue.
A number of mega trends have arisen inthe last decade that also havechallenged the pharmaceutical R&D process:
·Decline of R&D efficiency
The pharmaceutical industry has seen a steadily decline of R&D efficiencysince 1950 and thisis expected to be continuedgiven the challenging landscape.This is because while the number of new drugs launched by the industry has been constant, the costs per new drug havecontinuouslyincreased (see table below) due to the following reasons:
oNew technologies in drug research, such as combinatorial chemistry, DNA sequencing, high throughput screening,and computational drug design
oThe increasing size of clinical trials
oThe increasing costs for clinical infrastructure
oA greater complexity of clinical trials conducted fordrugs to treat chronic diseases
oA higher number of R&D personnel[16]
Figure 4:Total R&D expenditures of PhRMA[17]members from 1995-2012
Source:Schuhmacher(2015), p.58
Figure5:New molecular entitiesapprovedby FDA between 2001 and 2012 by major pharmaceutical companies
Source:Schuhmacher(2015), p.44
·Increasing difficulty of offering benefits over existing treatments
The space for big medical breakthroughs is limitedas many diseasescan bealreadysatisfactorily treated, even though the numbers of deaths from cancer, hard-to-treat diseases such as neurodegenerative or autoimmune diseasesand deaths from cardiovascular diseases are still large[18]resulting in more technically complex investigations for new drug targets and respective clinical trials.
·Stricter regulations by health authorities
Aside from the safety of a product, health authoritiesnowadays focuson whether a new drug is demonstrating benefits over existing treatment or not. This development is a result of theprice development in the past,demographic changes and an ageing population, which is a major challenge for public health funds in the future.New drugs are usually very expensive when they come to market and are under patent protection,leadingauthoritiestoquestion whether the high price is justified,and anew treatment optionmust clearlydemonstrateabenefit over the existing drugs.For example, countries like Germany and France have recently implemented changes in their health technology assessment (HTA) system that only allows price negotiations for drugswhich demonstrate a benefit over existing treatment options. Drugs without a superior benefit will be paid at a lower level/put into the fixed price system ordo not even get reimbursed.
·Payers are gaining more power
Global ageing and the rise in chronic diseases are causing a steady increase in demand for health services. This development is accompanied by the actual trend of payers gaining more power in determining market access for drugs and imposing pressure on revenues and margins to be able to keep up with thera-pidlyrising demand of health services and fewer financial resources.
3.2 Measures Big Pharma is taking to address the challenges
In order to be able to compete in this ever-changing environment and to steer in the opposite direction of reduced R&D efficiency, pharmaceutical companies have responded by the following measures:
Increasing the number of projects in the R&D pipeline
In order to continuously fuel the R&D pipeline and toachieve the industry´s goal of launching 2-3 new molecular entities per year to meet their growth objectives[19], pharmaceutical companies have heavily invested from a resource and financial aspect into an increased number of R&D projects. Since 2001, the total number of projects listed in the pipelines of pharmaceutical companies worldwide has increased from 5,995 (2001) to 11,307 (2013).[20]
Reducing Costs of R&D
Between
