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Home | Newsletter | UPDATE 2 | 2017 | “More Accurate Diagnoses Through Machine Learning” An Interview with Marco Rogg
July 19, 2017

“More Accurate Diagnoses Through Machine Learning” An Interview with Marco Rogg

As the ARCONDIS Senior Manager of Life Science Information Management, Marco Rogg is responsible for developing the division, especially in the context of the Digital Transformation. He has over 15 years of consulting experience and is an expert in Digital Transformation and IT strategies, with extensive knowledge of the life sciences industry.

Mr. Rogg, how do you see the future of the life sciences industry in information management? What are the challenges and opportunities?

Data is fundamental for establishing innovative business models such as “outcome-based pricing” and new treatment models such as “personalized health care”. The volume of data is increasing exponentially. This is driven in particular by raw data, so-called “high-dimensional data”. Such data is collected both during and outside of clinical trials, like for example OMICs data, but also additional biomarker and real-world data. If this data is stored centrally and is easily accessible and reusable, it provides valuable insights, finsights within the commercial sector, for example, such as how follow-up costs can be reduced. In clinical trials, biomarker data is becoming increasingly significant and is supplemented by the digital biomarker data that is being collected via apps and health trackers.

The challenge is clearly to gain an overview of these data sets and to make use of them in compliance with regulatory requirements. We regularly experience complex data structures in pharmaceutical companies, which hamper a broad use, to put it diplomatically.

This restricts cross-company use or leads to extensive additional efforts and time loss. For companies knowing how to deal with data growth and which are able to make data accessible and evaluable across all functions, new business opportunities are opening up. Due to the requirements to test drug combination therapies, clinical trials are becoming increasingly complex and the recruitment of sufficient numbers of test subjects (especially in rare diseases) is particularly difficult. This is where correctly prepared real-world data can make a big difference. In addition, machine learning approaches are increasingly used to identify patterns in these data sets and leverage them for other purposes in the company. Today, we find ourselves at an important turning point: Artificial Intelligence noticeably outperforms human ability in analyzing this kind of data.

 

What can your customers in Life Science Information Management expect from you? Where are you heading next?

As already mentioned, we are experiencing a wave of digitalization in life sciences. This provides opportunities for growth with the introduction of innovative services and business models, while it also comes with great challenges: new players like the Google subsidiary Calico are entering the market from the IT side and looking to compete with traditional life sciences companies.

Our commitment is to push and promote “Digital” and enable our clients to be successful in this transformation. We are already working with customers on innovation projects, such as new pricing models and digital biomarkers.

 

Accurate Diagnoses Through Machine Learning - Interview Marco Rogg

Why is ARCONDIS the right partner for the Digital Transformation?

We are doing so well because we combine our extensive life sciences know-how and interdisciplinary understanding with information technology expertise. To be more specific, our consultants possess life science expertise in the areas of research, development, and technical operations. We combine this with IT expertise and an understanding of compliance issues. It is this combination which allows us to successfully support the Digital Transformation of our customers. Therefore, I strongly support to expand this interdisciplinary understanding even further. It differentiates ARCONDIS and is an expression of our strength.

 

Accurate Diagnoses Through Machine Learning - Interview Marco Rogg

 

You mentioned innovation projects – could you tell us more about that?

In the case of digital biomarkers, this specific project deals with the development of apps and the use of wearables for the evaluation of digitally recorded data concerning the condition of a patient during a clinical study. We are currently working on these projects with our customers. We are also forging ahead with the development of a digital operating model for an international pharmaceutical company. We have developed a service catalog for digital services as well as an operating model that provides the agility required for innovation.

 

Whether it’s cloud platforms, internet of things or real world data – compliance always plays an important role for the life sciences industry. There is often a great deal of uncertainty as to how Digital Transformation can be reconciled with the regulatory requirements. What is your advice for pharmaceutical and medical device companies?

The key challenge is often the question: How can I combine digital innovation, which requires agility, with compliance, which often follows a traditional sequential waterfall model?

This is where agile validation can help. The main thing is to involve compliance departments in the planning process at an early stage to keep an eye on relevant regulatory requirements from the outset. This is where clients can benefit from the wide range of services offered by ARCONDIS. Every single consultant knows about the compliance requirements; it has become part of our DNA. Moreover, at ARCONDIS, we have around twenty consultants who are specialized exclusively in compliance and are also contributing greatly to agile validation. In other words, combining innovation and compliance is exactly what we are good at.

For the future, we are assuming that regulatory requirements will change drastically to keep up with technological advances, which will open the door for additional new digital business models. This process already started. A few years ago, for example, the use of fitness-tracker data was inconceivable. Today, as already mentioned, there are pilot projects based around the collection and evaluation of these readings, i.e., of digital biomarkers for clinical trials.

Advances in the field of digitization will continue to accelerate and lead to entirely new questions. For the near future, it is foreseeable that such systems will significantly help physicians to provide more reliable diagnoses. For many people, it is still unthinkable that one day the diagnosis will also be supported by artificial intelligence and, ultimately, might even be completely provided by it. An AI [editor’s note: Artificial Intelligence] can access more extensive data sets and will be able to make more informed diagnoses through ” machine learning “. This substantial advantage for patients coupled with rapidly rising costs in the health care system will create the necessary pressure to realize this change.

 

To round off, please complete the following sentence: To me, enthusing customers means …

… anticipating what the customer needs to be successful but which he is not yet aware of – this will help him to achieve his personal and company goals. As consultants, we see many complex customer situations and have the right experience to understand them and recommend the right measures.


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