PharmaTimes -
September 2019

In our cover feature this month (p20), John Pinching considers the need for pharma to secure meaningful and sustainable engagement with rare disease patients, and how the challenge of doing so is changing. The digital era, coupled with the evolving patient, has opened new channels of contact and communication, creating ideal conditions for the rise of rare disease communities and their closer interaction with pharma. Also on the rare disease theme, there’s a look at the promise of gene therapy on page 26.

Elsewhere (p23), Jennifer Bradford and Matthew Metherell consider the success and potential of artificial intelligence in clinical research. Real-world data harvested from electronic health records and other data sources, coupled with progress in machine learning, will play a key role in creating the next generation of clinical trials, they note. Aiden Flynn (p31) also explores how the collection and analysis of real-world patient data can be an ‘invaluable asset’ in clinical development, while  Janssen believes real-world evidence could realise an ‘efficient, personalised and truly patient-centric healthcare system’ (p28).

On page 34, AMPLEXOR’s Monika Vytiskova highlights the need for the transformation of translation management within the life sciences sector, and considers the potential of neural machine translation technology – already on the radars of most pharma companies – to vastly improve and accelerate the processing of data mined from myriad sources.

Also of particular note, there are just days left to sign up for the PharmaTimes 2019 Marketer of the Year, Communications Team of the Year, and Sales Awards competitions, as entry closes on September 16. To enter, or for more information, visit www.pharmatimes.com/competitions

I hope you enjoy the issue!

September 2019 - magazine highlights

Thumbnail image for The promise of gene editing

The promise of gene editing

Christopher Vakulskas says the rapid progress seen in gene editing is exciting, but there are still challenges in the field to overcome if its full potential is to be reached

Thumbnail image for Making sense of it

Making sense of it

As life sciences companies’ international ambitions grow, and global regulatory scrutiny in parallel, managing translated content is becoming ever more complex. So the promise of neural machine learning as a potential solution is appealing. But just how far can the technology go in reducing workloads and improving accuracy and turnaround times?

Thumbnail image for Changing tack

Changing tack

Think the old product launch playbook is still relevant? Think again.

Thumbnail image for Smart People: Pierre Bourdage

Smart People: Pierre Bourdage

Pierre Bourdage, global head of Biopharmaceutical Strategy & Portfolio Management at Sandoz, is flying the flag for biosimilars

Thumbnail image for The liberation of patient data

The liberation of patient data

Aiden Flynn explores how the collection and analysis of real-world patient data can be an invaluable asset in clinical development

Thumbnail image for The strongest link?

The strongest link?

Jennifer Bradford and Matthew Metherell consider the success and potential of artificial intelligence in clinical research and the impact of machine learning on clinical trials

Thumbnail image for It’s a small world

It’s a small world

To understand the full scope of a condition, pharma needs to appreciate the full tapestry of the patient experience. The challenge for industry in the realm of rare diseases, however, is to meaningfully engage with patients and convince them that they are an essential part of the research equation

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