Mein Abitur liegt nun bereits acht Jahre zurück – ich erschrecke jedes Mal, wenn ich nur darüber nachdenke. In den Jahren nach meinem Abschluss hat meine ehemalige Oberstufe ein Programm aufgebaut, bei dem frühere Schüler über ihren Werdegang und ihre aktuelle Position berichten. Ich unterstütze solche Aktionen sehr gerne und habe immer ein großes Interesse bei den Schülern wahrgenommen. Daher stand für mich sofort fest: In diesem Jahr bin ich wieder mit dabei. Jedoch wollte ich meine sehr einseitig gewordene Präsentation über Studieninhalte und Jobbeschreibungen etwas modernisieren – oder sollte ich sagen »digitalisieren«?
Und das hat sich gelohnt! Die Schüler sind dem Thema »Digitalisierung« offen, neugierig und mit Spaß begegnet und ich habe wertvolle Erkenntnisse über die nächste Generation gewonnen.
Introduction Big Data in the Life Science and Pharmaceutical Industry
A key driving factor in the life science and pharmaceutical industry is the possibility to handle large volumes of data in order to access, manage and analyze the data. To be able to gain business efficiency and a good performance, the drug development needs to take place in a best time to market relationship. Therefore, more completed clinical trials are necessary in a shortened timeframe. An acceleration in the drug development leads to an improved drug pipeline, less costs and faster product releases and therefore better profitability.
When introducing new systems or adding new areas to a new system usually data migrations are needed to integrate the data from the old system or other areas into the new system. During such data migrations often a migration tool is used to get the data from the source into the target system. This migration tool transforms the data to be compliant with the new system and imports the data into the system.
In such a scenario generally these questions come up: How to validate the data migration? Do we need to validate the tool itself? Do we need to validate all details of all rules and functionalities that are available in the tool and could be used in theory?
The implementation of a standardized DMS like D2 or the > Dell EMC Documentum Life Sciences Solution Suite requires the migration of documents from the old to the new system or a transforming of the data model within the system in order to work properly with the new application. Often this old data is not fully standardized and structured, but either based on a less controlled system such as Documentum Webtop or on a controlled system with slightly different structures such as CSC FirstDoc or Cara.
I’ve been in the Document Management System (DMS) / Enterprise Content Management System (ECMS) market for more than 20 years. Sometimes very focused on a specific aspect e.g. Technical Documentation, sometimes more general e.g. ECMS platform and sometimes with focus on an industry segment e.g. Life Science. I have seen a lot of vendors, products and technologies coming and going. The latest acquisition and certainly the biggest one was just a week ago. Hopefully, this will not reduce the power of innovation.
Mobile apps and Big Data are important topics, which are more and more relevant in the Life Science Industry. New media is available on a global base. That’s the reason why people and companies have to adapt their processes to this new digital age. People search for information on the internet and often trust blogs or forums more than the old fashioned ways. For medical problems they do not only trust doctors, but inform themselves on the web. The new social media has big influence on the ways on how information is provided and received. Also the way of interactive information exchange has changed. Formulas are used in a digital way, either on websites or also on mobile apps. Therefore data has to be accessed in a global way. Mobile apps are used outside of secure networks; therefore, also the related data has to be stored secure in a global way, which allows access from the internet.
Although both industries – Discrete Manufacturing and Process Manufacturing – are completely different, I see some similarities.
10 years ago, the only competitive threat for a traditional OEM came from another traditional OEM. All R&D Managers had an arrogant smile on the face when they heard about a small US company, which was entering the market with electric cars. Today this company – Tesla – is also an established player. But new competitors do appear on the horizon: Apple, Google, Uber and others. Companies with no knowledge about how to build, sell and maintain a car. Why is this possible?
The extensive procedural requirements of the U.S. courts for companies active on the American market were in place even before the recent Volkswagen exhaust scandal. However, the life sciences sector is affected by the e-discovery requirements just as much if not more so than the automotive industry that is currently the focus of attention. Plaintiffs were granted powers similar to those of state prosecutors with the amendment of the Federal Rules of Civil Procedure (FRCP) in 2006 – and not only in product liability lawsuits. Requests for information were expanded to include electronically stored information (ESI) which has far-reaching consequences for how information is handled in the company. A plaintiff (with the support of the courts) may demand the surrender of all relevant ESI from the defendant. This applies to standard e-mails as well as Office documents and text messages on smartphones, online content, and social media posts. Failure to deliver the information within the imposed deadlines or even the inability to identify relevant information and safeguard it against changes can lead to heavy penalties and the loss of the case, regardless of how the evidence may point. Public authorities and other jurisdictions are increasingly expecting compliance with e-discovery standards within the scope of requests and investigations as well. Only certain procedures are now being accepted for internal searches and the evaluations of documents. read more
Virtually every industry is currently facing the challenge of digital transformation, including the life sciences sector.
But what exactly does the digital transformation entail and what consequences does it have?
When it comes to digital transformation, we talk about the ‘third wave’ of IT. The first wave was the introduction of the server-client architecture which followed the mainframe principle. The second wave was Internet technology, and we are now talking about a third wave, that being smart, networked devices.
As I see it, digital transformation is based on two main pillars:
- On the one hand, we are finding that the pace of sensor development is gaining speed. They are becoming more accurate, more specialized, and more compact. But most of all, they are growing more affordable, meaning they can even be used as disposable products. Sensors are used everywhere, whether in industry, in cars, at home, or in the field of medicine. They measure sounds, vibrations, movements, temperature, pressure, humidity, and much more.
- The second factor is that IT is now readily available and easy to consume in any quality and quantity and at any time. The vast amount of data produced by sensors, mobile end devices, traffic management systems, and much more can nowadays easily be stored centrally and can be analyzed in a matter of seconds, in some cases even in real time. Correlations obtained from these data produce unprecedented findings about such matters as production processes, causes of illnesses, and the usage of wearables.
The digital transformation is driving industry change
These new findings are putting many companies in a position to rethink their business processes and models: read more