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Volume 37 Number 11 December 2019 VOLUME 37 NUMBER 11 DECEMBER 2019 OUTLOOK TABLE OF CONTENTS OUTLOOK ■ FROM THE EDITOR There is much to discuss about the future of the biopharma, medtech and generics sectors as SCRIP 100 2 we enter a new year and new decade. Outlook 2020 includes annual league tables for both the top 100 biopharmaceutical and top 100 STRATEGY 14 medical technology companies, as well as anal- ysis of the leading generics and biosimilars businesses. Alongside this performance as- LEADERSHIP 30 sessment of the key markets covered by In Vivo and its sister publications – Scrip, Pink Sheet, Medtech Insight and Generics Bulletin – our LUCIE ELLIS special issue takes a deeper dive into key R&D 38 EXECUTIVE EDITOR themes disrupting today’s corporate strategies and paving the way for innovation. CLINICAL TRIALS 46 Explore within Outlook 2020 what “company culture” really means in phar- ma against a backdrop of intense pressure from investors for greater top- line growth. Hear from leaders at Alexion how they have restructured the company’s R&D business and rejuvenated the pipeline. And get an expert POLICY & REGULATION 50 view on how to prepare for oral explanations for regulatory submissions. Within the medtech realm, Outlook 2020 outlines the performance of key GENERICS & BIOSIMILARS 64 device and diagnostics players alongside expectations for the coming 12 months. Also featured are articles exploring the changing landscape in Chi- na, and how the confluence of health and technology will transform care in the 2020s. MEDTECH 82 New for 2020 are chapters on Strategy and Digital Transformation and what they mean for the biopharma and medtech industries. MANUFACTURING 96 In Vivo’s Outlook 2020 edition looks across all of the key health care sectors and connects the dots: pharma, biotech, devices, diagnostics, generics, bio- similars and health tech. DIGITAL TRANSFORMATION 102 SPONSORS ® December 2018 | In Vivo | 1 ■ SCRIPSCRIP 100 SCRIP 100 ■ of therapies for adverse events, addressing and adapting to changes Clinical trials are increasingly designed with mobile and sensor 7 SPONSORED BY: in sites for patient recruitment, and using EHRs to reduce data errors. technologies – such as smartphone applications, wearables and im- plantables – to capture data. The reliability and accuracy of these de- Meanwhile, blockchain has potential in addressing a key concern vices could mean that real-time monitoring of patients participating in in clinical trials – data integrity. Responding to queries from clinical trials could be used to demonstrate the health economic value regulatory authorities regarding maintaining the integrity of of protocols, drugs and devices. For instance, a wearable might include Transforming Clinical Trials trial results from data capture is often a time-consuming burden. an accelerometer. Applying various algorithms to the accelerometer Designing blockchain into a clinical trial – which can show data signals could generate data on sleep quality, steps per day and other from their origin to the final report – has the potential to accelerate endpoints that reflects real-world experiences of trial participants.11 With Digital Tech, And What the regulatory approval process and reduce costs.8 CONCLUSION INCREASED USE OF DIGITAL TECHNOLOGY That Means For The Patient Despite the benefits of digital technologies, leveraging their FOR PATIENT-CENTERED DESIGN potential requires the right infrastructure and expertise. In fact, Many stakeholders within the pharma and biotech industries are management systems, safety systems and data repositories. A Employing digital technologies can also simplify the patient experi- applying advanced statistical and trial design to specific study witnessing radical shifts taking place in how clinical trials are central data storage location provides sponsors and sites access ence in clinical trials. Real-time monitoring of data collected from de- needs was one of the top-three challenges sponsors identified that conceived, designed and conducted. This transformation relies in real time, and increases productivity by allowing information vices and sensors could mean less frequent study visits for patients. In requires the skills and knowledge of contract research organiza- heavily on applying the power of digital technologies. to be quickly shared and managed in a secure fashion. addition, collecting data points throughout a clinical trial could assist tions (CROs) and other clinical trial experts. sponsors in making go/no-go decisions faster, saving time and costs. As new technologies emerge, they will converge through networks Additionally, the continuous streaming of data to cloud-based plat- CROs can develop platforms to securely capture, transmit and visual- and cloud-based platforms to create a new digital health care ecosys- forms could accelerate clinical trials and decrease protocol amend- Within clinical trials, patient data are transactional between ize medical device data and can support volumes of data collected by tem. Collectively, they will have a greater impact on clinical trials than ments, resulting in reduced clinical trial costs. Also, sponsors can use stakeholders such as health care institutions, patients and regula- sensors. Identifying and addressing these current study needs using any one technology would achieve separately. At the center of this cloud-based platforms for data submission to regulatory agencies, tors. As more patients become aware of how their data are being data, AI and other novel digital technologies not only improves trial ecosystem is the patient, demonstrated by the uptick in personalized which has the potential to accelerate drug development, streamline used, harnessing blockchain technology could help maintain efficiency significantly in the near term, but also builds competence therapies and a growing emphasis on patient-reported outcomes. regulatory review and enhance regulatory decision-making.2 patient confidentiality – an ethical and legal requirement – and and confidence in applying the digital technology needed to succeed will become more important in engaging and retaining patients. and increase return on investment in the trial of the future. While the mean projected return on new drug research and devel- DEMOCRATIZATION OF AI, DATA AND ALGORITHMS REFERENCES opment (R&D) investments by a dozen large cap biopharma firms Blockchain’s potential to increase security, privacy and interoper- 1. Terry C., Lesser N. Unlocking R&D productivity: Measuring the return from pharma- fell from 10.1% in 2010 to 1.9% in 2018, 1 an opportunity remains The influx of big data is fueling algorithms that are the building blocks ability of health data could make EHRs more efficient and secure. ceutical innovation 2018. Deloitte Centre for Health Solutions, 2018. Retrieved from: for emerging digital technologies to improve R&D productivity. of AI, machine learning and other technologies, such as blockchain. With blockchain, an audit trail is built into the transaction of data, https://www2.deloitte.com/content/dam/Deloitte/uk/Documents/life-sciences- health-care/deloitte-uk-measuring-return-on-pharma-innovation-report-2018.pdf The democratization of data, especially real-world data, is inevitable allowing verification of the original source of the information, as 2. Robertson, A.S. et al. Cloud-based data systems in drug regulation: An industry We predict the following four technology trends will impact the as its use spreads across every aspect of drug and device development. well as the ability to detect attempts to tamper with it. perspective. Nat. Rev. Drug Discovery, November 11, 2019. doi: 10.1038/d41573- drug and device development industries and have the potential 019-00193-7. Retrieved from: https://www.nature.com/articles/d41573-019-00193-7 3. Digital disruption in biopharma: How digital transformation can reverse declin- to transform pharma R&D: As analytic methods improve, these approaches will have a com- Also, blockchain allows for greater data availability. When data ing ROI in R&D. ICON plc, 2019. Retrieved from: https://www.iconplc.com/ • Rising use of the cloud pounding effect on the industry, ultimately increasing efficiency. are shared openly within a network, there are fewer issues with insights/digital-disruption/digital-disruption-in-biopharma/ • Democratization of artificial intelligence (AI), data and algorithms AI-powered capabilities, including pattern recognition and evolu- data system interoperability. For example, availability and acces- 4. Reh G. et al. 2019 Global life sciences outlook: Focus and transform – accelerating change in life sciences. Deloitte Touche Tohmatsu Limited Life Sciences and Health • Incorporation of the Internet of Medical Things (IoMT) tionary modeling, are essential to gather, normalize, analyze and sibility of patient information could be used for patient feasibility Care, 2019. Retrieved from: https://www2.deloitte.com/content/dam/Deloitte/ • Increased use of digital technology for patient-centered design harness the growing masses of data. In ICON’s industry survey, AI analysis and population studies. Moreover, blockchain allows global/Documents/Life-Sciences-Health-Care/gx-lshc-ls-outlook-2019.pdf and advanced analytics were viewed as the digital technologies researchers to submit queries for data that are stored off chain, 5. Kalis B. 10 AI applications that could change health care. Accenture, Har- vard Business Review Visual Library, 2018. Retrieved from: https://hbr. Understanding the potential of these emerging
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