Mind the gap: Overcoming a common blind spot in IP portfolio valuation

The value of an organization's intellectual property (IP) portfolio has become an intangible asset of innovation-focused organizations. As the volume and value of IP-driven business transactions increase, financial valuation of IP portfolios is becoming a critical discipline. Valuations are used to advise in acquisitions, patent portfolio adjustments, licenses or litigations. However, the most common IP valuation methods in use today have a blind spot that could be driving undervaluation of key patents.

Mind the gap: Spanning the divide between patents and journal articles

There's no doubt that the differences between journal articles and patents are extensive and impact how they can be searched. Tools that provide a unified approach to curating journals articles and patents are key to overcoming the search gap and driving innovation forward.

Tips to avoid patent pitfalls as market for RNAi-derived therapeutics grows

The value and complexity of the patent landscape around RNA interference (RNAi) is increasing, creating special challenges for patent searches to protect IP and maximize its value. Learn how CAS can help with an IP search on RNAi or other emerging technology areas.

Data, the cornerstone for successful digital transformation in R&D

How can you make smart investments that position your organization for success with today's technologies, such as deep learning, as well as the next breakthroughs? This blog will show you how building a solid data foundation is essential to long-term success in implementing digital technologies and how you can get started with smart investments today that will pay dividends long into the future.

Avoiding Costly IP Missteps: Insights for high-quality due diligence searches

New findings reveal innovation in small molecule discovery is accelerating

Though an increasing number of novel chemical compounds are being synthesized each year, there is growing concern that innovation may be stagnating in small molecule discovery. However, new research published by CAS scientists in the October 2019 Journal of Organic Chemistry reveals that the pace of small molecule innovation is actually accelerating from a structural perspective and offers insights into finding fruitful new areas for further investigation as chemists navigate a vast and largely unexplored chemical space.

Data modeling: A fundamental pillar of your future AI technology

How your data is organized and stored, and the data relationships within, is defined by a data model. An effective model allows users across your organization to easily understand how the business operates. It is the linchpin of almost every high-value business solution, with its greatest value realized when applied beyond the boundaries of individual lines of businesses (LOBs) or operations within an organization. This data model is a strategic pillar for information management, upon which the success of future business-critical projects depend.

To optimize machine learning predictions, it is best to keep a chemist in the loop

Read how machine learning is being used to identify, screen and prioritize candidate compounds. CAS demonstrates how a machine learning approach will increase accuracy and reliability of predictions.

Accelerating innovation in materials science with machine learning

Given the wide range of applications and benefits offered by ML, there is a current push to implement it in the materials science sector, with many R&D-based organizations investing heavily in the development of digital strategies. However, one challenge these teams face is that scientific data is often complex and disconnected. This is a problem because ML systems rely on well-organized, high-quality data. So, how can you effectively apply ML to accelerate innovation and growth in your materials science company?