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Pranav Kumar

Dassault Systèmes Acquires Medidata to Ride the Platform Wave in Life Sciences | Blog

By | Blog, Healthcare & Life Sciences, Uncategorized

When news first hit in late April 2019 of speculation around Medidata Solutions being acquired by Dassault Systèmes – a France-based software company that develops 3D design, 3D digital mock-up, and product lifecycle management software – Medidata’s stock value went soaring. The deal immediately made sense. The fact that Dassault Systèmes was looking to ramp up its offerings for life sciences companies made Medidata, which we recently recognized as a Leader and Star Performer in our PEAK Matrix™ for Clinical Trials Products 2019, an attractive acquisition prospect.

 

Everest Group Life Sciences Clinical Trials Products PEAK Matrix Assessment 2019

 

Fast forward to June 2019 and the deal is done. The all-cash transaction is valued at US$5.8 billion and represents Dassault Systèmes’ largest acquisition to date. It will finance the deal with a €1 billion loan, a €3 billion bridge-to-loan facility, and available cash. It’s the first time the French company has resorted to external funding, which only accentuates how much it prizes Medidata as an asset.

The strategic intent behind the deal

Dassault Systèmes began focusing on the life sciences market a few years ago with the vision to improve the penetration of digital technologies in the industry. Its last life sciences-focused acquisition was that of Accelrys in 2014, which helped Dassault Systèmes establish BIOVIA, its brand for biological, chemical, and materials modeling and simulation, research, and open collaborative discovery.

With the acquisition of Medidata Solutions, Dassault Systèmes makes a statement that it is serious about achieving this vision. The acquisition will make life sciences Dassault Systèmes’ second largest industry focus, after transportation and mobility. Medidata grew at a CAGR of 17 percent during 2015-2018, driven by its dominance in electronic data capture through its flagship product, Rave.

Dassault Systèmes prides itself on its 3DEXPERIENCE platform, which is meant to enhance digital collaboration in complex sectors like aerospace, infrastructure, and mobility. Dassault Systèmes now looks to extend these benefits to life sciences. By adding Medidata’s clinical and commercial offerings to its own 3D experience expertise, Dassault Systèmes aims to create a platform that offers complete digital continuity to the life sciences industry, addressing complex challenges such as personalized medicine and patient-centric experiences.

Unpacking the companies’ synergies

Synergy area

Dassault Systèmes

Medidata Solutions

Value proposition

 

Design, modeling, and visualization software, with leading capabilities for the aerospace, defense, and consumer goods industries. Dassault Systèmes now aims to bolster its life sciences division

 

Life sciences clinical and commercial software pure-play, with deep domain expertise and strong consulting pedigree

Coverage of the life sciences value chain

 

Drug discovery, manufacturing, and supply chain Clinical and commercial operations

Key technology offerings

Design, modeling, simulation, and virtualization software Data capture, real world evidence, advanced analytics, AI-driven insights, and operations management

Customers

Customers are mostly in the aerospace, defense, and consumer goods industries

Sizable number of European life sciences clients, including medical devices firms such as Medtronic, FEops, Novo Nordisk, and Kavo Dental

1,300 life sciences companies, three quarters of which are in America. This includes most of the Big Pharma and CRO firms

Product coverage across the value chain

Product coverage across the value chain

Key opportunities

Dassault Systèmes is sitting on a lot of cash. This will give Medidata the financial muscle it needs to make the right investments in talent and technology to compete with the big players like Oracle Health Sciences and Accenture.

The integration of capabilities could lead to the creation of a unique end-to-end platform for life sciences across the entire value chain. Medidata has clinical and commercial capabilities, and Dassault Systèmes has offerings for drug discovery, manufacturing, and supply chain.

Potential risks

It’s not clear how the integration of Medidata’s products with the broader 3DEXPERIENCE platform will take place. It could be a challenge linking Medidata’s clinical trials and commercial operations solutions with Dassault Systèmes’ design and visualization offerings.

Dassault Systèmes’ has diversified offerings across several industries. In the long run, this may dilute Medidata’s brand image as a leader and focused player for clinical trials technology.

Closing thoughts

The life sciences industry needs aggressive digitalization to realize efficiency gains and reduce the lengthy timelines between drug conceptualization and drugs reaching the market. We’ve seen technology vendors coming up with integrated solutions for clinical trials to help enhance trial efficiency. While the need for a platform is evident, technical debt and change management issues hinder this platform-centric vision. This is a high growth market, which is likely to attract more interest in the coming 18-24 months. More SaaS companies will need to pivot to the platform conversation to scale and remain relevant. We will be tracking this space closely.

Artificial Intelligence is Democratizing Mental Health | Sherpas in Blue Shirts

By | Blog

If I had a penny for every time Artificial Intelligence was mentioned during the recent NASSCOM India Leadership Forum, I could buy a lot of Bitcoins. Both hype and hope abound around AI and its impact on different industries’ business models.

Let’s take a look at AI the healthcare industry. Adoption is increasing, helping solve a number of problems for patients, doctors, and the industry overall. AI engines are helping doctors identify patterns in patient symptoms with data and analytics, improve diagnoses, pick the right treatments, and monitor care.

For instance, physicians can now plug diagnoses into IBM’s Watson for Oncology and receive treatment suggestions based on historical patient data and information from medical journals. Face2Gene combines facial recognition software with machine learning to identify facial dysmorphic features, helping clinicians diagnose rare genetic diseases.

Mental health treatment: Can AI be the cure?

Using AI to treat mental health issues is particularly fascinating. So far, AI has only been viewed as a means to help healthcare professionals provide better care. But can it eliminate a patient’s need to consult with a doctor altogether for mental health-focused moral counseling and empathetic support?

Consider this: AI engines today have the ability to listen, interpret, learn, plan, and problem solve. Early identification of mental health issues is possible through the analysis of a person’s facial features, writing patterns, tone of voice, word choice, and phrase length.

These are all decisive cues in learning what’s going on in a person’s mind, and can be used to predict or detect and monitor mental conditions such as psychosis, schizophrenia, mania, and depression.

AI as a panacea for mental health

The idea of end-to-end mental health treatment through AI with no human intervention is quite viable, and the prospect becomes even more enticing when you consider how the following factors could drive acceptance among patients:

AI Blog ExhibitThus, it’s not surprising that a few players have already begun to delve into this space. Woebot is a software chatbot that delivers a mood management program based on Cognitive Behavior Therapy (CBT). AI luminary Andrew Ng is on the company’s board of directors. Randomized controlled trials at Stanford University have shown that Woebot can help reduce symptoms of depression and anxiety in two weeks.

AI Blog MobileAnother example is Tess, a psychological AI that communicates via text, administers highly personalized psychotherapy, psycho-education, and delivers on-demand health-related reminders, when and where a mental health professional isn’t available. It can hold conversations with the patient through a variety of existing technology-based communications, including SMS, WhatsApp, and web browsers. More recently, Facebook started using AI to help predict when users may be suicidal.

There are even cases of highly specialized products:

  • An app called Karim counsels Syrian refugee children
  • Emma helps Dutch speakers with mild anxiety
  • MindBloom allows users to support and motivate each other

Are robo-doctors just around the corner?

While the hype crowd might have you believe that your next appointment will be with a droid, several open questions warrant healthy skepticism of mainstream AI adoption in mental healthcare:

  • There are privacy issues, with the possibility of user data being shared with various parties seeking to profit from it
  • Could training AI systems with biased data lead to them make biased decisions?
  • Will users even take advice from software as seriously as they would from a qualified professional?
  • Can the technology successfully cater to a universal population?

The ecosystem is trying to solve for these and other questions. While it might be too early to say that AI-based mental health treatment options can become mainstream currency, they clearly create significant value. As healthcare organizations and patients experiment with these use cases, there’s a sizable opportunity to reimagine the workflow and treatment paradigm.