Technology

Tim Willis and Oliver Wack outline the role of alternative data in supply chain risk management, and the ancillary benefits that come from adopting such technology.

Rick Krohn talks to Pharm Exec about the pharma applications of one of tech’s hottest solutions – blockchain.

Drug discovery to development through commercialization.

Pharm Exec’s annual look at what lies ahead for the biopharma industry in the coming months examines eight key trends that are seemingly at tipping points in their evolution and poised to shape the life sciences landscape in 2019.

Pharma companies are increasingly expanding their portfolios into digital health solutions. To find the right partners, there are several key considerations that inform their evaluation and selection.

Leaders at Novartis share how the big pharma is laying the foundations for a potential new operating model as a "medicines and data science company."

As part of its digital transformation, last year Novartis recruited Raj Patil, as Head of Data Strategy, and Shahram Ebadollahi as Head of Data Science and Advanced Analytics. Here they talk to Pharm Exec about the task that lies ahead.

Andre Heeg, Sandor's new Head of Digital, tells Pharm Exec about his digital vision for the company.

Ashley Slavic details how Veeva Systems prepared for the EU data protection regulation, and what others can learn from the experience

Pharm Exec speaks to Mark Lambrecht, Director of the Health and Life Sciences Global Practice at SAS, about the growing role of big data analytics in pharma and how the industry is evolving to keep pace with it.

Almost a year and a half later, key understandings have emerged to help companies better combat future data-breach attempts.

Sonalee Agarwal, head of value and evidence strategy for Alnylam, talks with Pharm Exec about the role of real-world evidence in the rare and ultra-rare disease space.

In pharma, there may be hope that companies' and the industry's ability to adapt to change may finally be catching up to the pace of new and intelligent uses of technology and clinical data.

How artificial intelligence, wearable devices, and translational informatics are changing healthcare.

Pharma companies now need to identify areas where AI can be applied to the digital initiatives of every pharmaceutical marketer as they strive to reach physicians with precision and usefulness, writes Gaurav Kapoor.

Keshia Vaughn looks at how machine learning can transform commercial planning and outlines what teams will need to deploy it effectively.

Emil Eifrem examines how life science researchers at Munich’s German Center for Diabetes Research are uncovering insights in their data with a new way of working with complex data

Although it is unlikely that mock demonstrators will be seen at any drug information or regulatory conferences, pharmacovigilance software is indeed having its “Salesforce” moment.

The next generation of supply chain shows an increasing need for blockchain technology.

As pharm execs look to real-world data to aid in translational research and close the gap from traditional clinical trials to real-world efficacy, there are three foundational pillars to build from. Bill Fox reports.

AI has become ubiquitous in all industries, including life sciences. But is also attracting some concerns – particularly around job losses, ethics, and more broadly, how successful it really is, writes Steve Arlington.

Karim Damji discusses how Artificial Intelligence (AI)-informed Systems of Intelligence and Virtual Assistants offer powerful solutions to the common struggles pharma companies face today.

Daniel Gold looks at the benefits of centralising an organization's data in a core repository and adopting a comprehensive business intelligence strategy.

Brands should look to their agencies to be a true data-driven business partner, not just a creative partner, writes Kevin Troyanos.

There’s a growing realization that advances in connected devices, sensors and predictive analytics represent a game-changer when it comes to patient support programs (PSPs), writes Jim O'Donaghue.

For pharma leaders, AI can bring about a new reality of seeing a multitude of possible paths, forecasting the interplay of multi-dimensional trends, and charting patient journeys that are based on reality, writes Aswin Chandrakantan.

With specialty companies getting smarter in applying their big data insights to product marketing, the true commercial potential of machine learning and predictive modeling may soon be within reach.

An overview of Orphan Reinsurer and Benefit Managers groups, including potential challenges with the model and various model suggestions.

How pharma companies are leveraging natural language processing (NLP) for rapid and effective handling of unstructured text.