<\/p>\n
Current Challenges<\/strong><\/p>\n Since losing patent exclusivity of its blockbuster Multiple Sclerosis drug, Copaxone, in 2015, Teva Pharmaceuticals has lost over $50B in market cap. 1<\/sup>,<\/sup>2<\/sup> Recent news rival generics manufacturer, Mylan, will receive earlier than anticipated FDA approval for its generic 40mg three times weekly formulation will further challenge Teva\u2019s top line.3<\/sup> \u00a0Over the same period, consolidation in the PBM space and increased generic competition is diminishing already thin margins for small molecule drugs.3<\/sup> These events captured the attention of activist investors, and in response, Teva leadership committed to divest non-core assets to fund business operations and to focus on operational efficiencies to manage the bottom line. 4<\/sup>,<\/sup>5<\/sup>,<\/sup>6<\/sup>,<\/sup>7<\/sup>,<\/sup>8<\/sup><\/p>\n Teva pursued multiple strategies to mitigate the impact from Copaxone generic entrants upon loss of exclusivity. These strategies, outlined at Teva\u2019s 2012 investor meeting, included (1) expanding its pipeline of higher margin branded therapies, (2) focusing on its biosimilar therapy pipeline, and (3) improving global supply chain efficiency. 6,7 <\/sup>Common across of these initiatives is the increasing use of \u201cdigitization\u201d to drive efficiency and value for the organization. Early examples of Teva\u2019s use of digitization across its supply chain included:<\/p>\n Near-Term Opportunities<\/strong><\/p>\n More recently in 2015, Teva made several investments and established multiple partnerships in digital health, and should expect to realize the benefits of these solutions over the next few years.<\/p>\n One of the first partnerships established was with IBM\u2019s Watson Health. Specifically, IBM-Teva hopes to use machine learning in the Watson Health Cloud to analyze chronic disease models that facilitate drug innovation, reduce drug misuse, and to increase medication adherence using real-world evidence. 1<\/sup>3,<\/sup>14<\/sup><\/p>\n In addition to the digitization of therapeutic development, Teva is also innovating its biosimilar supply chain through a partnership with cold chain logistics leader, Controlant.15,16<\/sup> Teva and Controlant have been recognized across the industry for their use of wireless temperature monitoring systems to track biologics distribution end-to-end; in the future, this partnership could serve as a strategic differentiator for Teva to compete against manufacturers of branded biologics and biosimilars.15,16,17<\/sup><\/p>\n Other areas of investment include drug delivery technologies that can collect real-world patient data and differentiate generic drugs.\u00a0 In the near-term, Teva is expected to commercialize its Gecko Health CareTRx \u201csmart\u201d inhaler and mobile-app to track compliance across its respiratory therapies.18<\/sup> Teva also invested in Microchips Biotech, a unique implantable drug delivery device that can be wirelessly programmed to deliver desired amounts of medication.19<\/sup> Additionally, Teva partnered with Intel to use their Trusted Analytics Platform to wirelessly collect Huntington\u2019s Disease patient data as a part of its Phase 2 study to monitor declines in motor control over time.20<\/sup><\/p>\n Finally, Teva\u2019s investment in American Well, a telehealth company that plans to add mail order medications could expand the number of patients with access to care while also providing Teva with a more direct channel to the patient.21<\/sup> \u00a0In the near to mid-term, this solution could increase access to care while replacing traditional doctor\u2019s office visits and retail pharmacies.<\/p>\n Mid-Term Opportunities<\/strong><\/p>\n Teva partnered with Phillips and formed Sanara Ventures, a joint venture to invest in strategic health technologies.22<\/sup> Sanara\u2019s investments in several focus areas should further enable Teva to use digitization to increase demand for its products and to maintain market share and competitive pricing in the mid-term. Focus areas for the venture group include:<\/p>\n Long-Term Recommendations<\/strong><\/p>\n In the long-term, Teva has the opportunity to move up in the supply chain, closing the gap between drug manufacturer and patient. Teva should look for new ways to leverage data from connected drug delivery devices and sensors to develop predictive analytics that could prompt clinicians\/patients to titrate or change medications, preventing disease worsening and costly acute care. Additionally, Teva should use these devices in clinical studies as way to economically collect additional clinical patient data. Finally, Teva should increasingly use this patient data in contract negotiations with pharmacies and insurers to demonstrate the value of its therapies.<\/p>\n With a strong pipeline of digital health solutions, how else might Teva use these technologies to close the gap between Teva and the ultimate consumer, the patient?<\/p>\n How could Teva use connected drug delivery devices to better forecast their product demand?<\/p>\n <\/p>\n Word Count: 797<\/em><\/p>\n <\/p>\n Citations:<\/u><\/p>\n Notes:<\/p>\n <\/p>\n","protected":false},"excerpt":{"rendered":" Connected drug delivery devices are among the many digital supply chain innovations Teva has acquired to drive sales and control operational costs<\/p>\n","protected":false},"author":10020,"featured_media":25801,"comment_status":"open","ping_status":"closed","template":"","categories":[2412,50,4004,2418,843,346,1686,3730,1213],"class_list":["post-25800","hck-submission","type-hck-submission","status-publish","has-post-thumbnail","hentry","category-clinical-trials","category-cloud-computing","category-cold-chain","category-drug-development-process","category-generics","category-machine-learning","category-pharmaceutical","category-pharmacy-benefit-manager","category-social-networking","hck-taxonomy-organization-teva-pharmaceuticals","hck-taxonomy-industry-pharmaceutical","hck-taxonomy-country-israel"],"connected_submission_link":"https:\/\/d3.harvard.edu\/platform-rctom\/assignment\/rc-tom-challenge-2017\/","yoast_head":"\n\n
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