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In this blog piece, we explore how Derek Nexus performs when evaluated against 7 different in silico skin sensitisation models.

Artificial Intelligence (AI) has become a powerful force within the pharmaceutical industry, catalysed by the challenging lengthy and costly drug development process. To maximize the impact of AI, it is critical to have access to enough good quality data to allow machine learning algorithms to extract relevant knowledge and produce valuable models.

Are you interested in using your data to anticipate and mitigate adverse drug reactions? The Effiris consortium - currently composed of Takeda, GSK and UCB - is working to achieve just that.

In his blog “Human review of in silico predictions of toxicity”, Principal Scientist, Alex Cayley, outlined the reasons why expert review is essential when using in silico tools to assess toxicity, particularly in the ICH M7 use case where expert review of two complementary in silico systems is required [1].

In this post we discuss how consideration of the user’s journey led to Lhasa tackling the ICH M7 use case with a brand-new automated workflow, now available to Derek and Sarah users in Nexus 2.3. I’ll also show some worked examples of results from the new system.

Key to the regulatory acceptance of purge arguments is the conservatism within the purge factor scoring system, which for reactivity purge has been demonstrated across a number of publications and is consistently implemented across the pharmaceutical industry through the development of a collective understanding of and how they should be applied.

Likewise, when volatility purge scoring is relatively simple to understand and apply, particularly using the scoring thresholds originally proposed by Teasdale et al.

However, through our interactions with Mirabilis users, regulators, and other members of the purge community, it has become increasingly apparent that the same cannot be said of solubility purge scoring. Lhasa have therefore identified the huge value to the community of developing an accepted best practice, incorporating both the application of solubility purge scoring and, where appropriate, provision of a clear justification of the purge factor assigned.

Coronaviruses are a large family of viruses which can affect humans or other species and can range anywhere from a mild illness such as the common cold to more severe illnesses such as Severe Acute Respiratory Syndrome (SARS). Coronavirus disease 2019 (COVID-19) is an infectious disease caused by the novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2).

In a world where we are all striving for progress, technology is also advancing quickly.

Like many organisations across the life sciences industry – evidenced by the 82 Amazon Web Service (AWS) life sciences case studies -  Lhasa has adopted cloud, Software as a Service (SaaS), options across three notable areas...

Are you getting the most out of Zeneth, Lhasa’s expert, knowledge-based in silico software for the prediction of forced degradation pathways of organic active pharmaceutical ingredients (APIs)? 

“Our technology is designed by scientists, for scientists, in collaboration with industry stakeholders and regulators” …

At Lhasa Limited we often talk about the importance of industry and regulatory input in shaping our scientific direction. This article discusses a few key areas of involvement and collaboration plus, focuses on a recent example, on the topic of Adverse Outcome Pathways (AOPs). Read on to learn more and find out how you can get involved!