Innovate

The introduction of purge arguments by Teasdale et al. has had a huge impact on the way in which companies consider the quality of their drug substances with respect to potentially mutagenic impurities (PMIs), allowing chemists to utilise their inherent knowledge of the physicochemical properties of the impurities within the synthetic process.1 This encourages a […]

The saying goes, “It takes a village to raise a child”. This sentiment can be translated to the work we do at Lhasa Limited, particularly to the work which we put into building Adverse Outcome Pathways (AOPs). To echo the sentiment in Chris Barber’s previous blog post, The challenge of building QSAR models; it is

Creating great software is a balance between multiple perspectives where favouring one perspective may be detrimental to another perspective. To add further complexity, these perspectives will vary depending on the project, the organisation, the team, or even the day. That said, there are a number of attributes to writing great software that are common to

The recent discovery of N-nitrosamine (nitrosamine) impurities in several marketed pharmaceuticals has led to a requirement for further investigation into nitrosamine mutagenic and carcinogenic activity. Updated regulatory requirements mean that marketing authorisation holders for human medicines, containing chemically synthesised active substances, must review their medicines for the possible presence of nitrosamines and test all products at

In May, Lhasa hosted a webinar titled; The Application of Adverse Outcome Pathways (AOPs) for Risk Assessment. In case you missed this event, Senior Scientist, Alun Myden has provided an overview of the presentation and the work which Lhasa is doing in this area. An Introduction to AOPs AOPs are a formalised approach to documenting mechanisms

The concept of pre-competitive collaborations and data sharing is currently in sharp focus with the current global collaborative efforts to combat Coronavirus, where the sharing of scientific knowledge is both urgent and critical for us to have a better chance of tackling the global pandemic. From the inception of Lhasa Limited in 1983, we’ve sought

Coronaviruses and SARS-CoV-2 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

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. Despite the availability

Human Review of In Silico Predictions of Toxicity: Some Key Questions for Consideration When Making An Assessment The speed by which models for toxicity prediction can be built and the accuracy with which they make predictions, have both improved greatly in recent years as a result of advances in technology, mechanistic understanding and access to

Building QSAR models is easy. Building useful QSAR models is harder. Building QSAR models you can trust – well that can be really challenging – and this is where a lot of Lhasa’s effort is dedicated – creating models that can be used with confidence to make big decisions – such as those made during a