Innovate

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 > 80 Amazon Web Service (AWS) life sciences case studies –  Lhasa has adopted cloud, Software as a Service (SaaS), options across three notable areas: Mirabilis – reducing analytical testing by […]

Are you interested in collaboratively using data to predict and avoid adverse drug reactions? The Effiris consortium – currently composed of Takeda, GSK and UCB – is working to achieve just that. The project aims to help pharmaceutical organisations accelerate drug discovery through machine learning. Many readers will be very familiar with the fact that one

Lhasa Limited, in collaboration with Leadscope, Inc., are leading a working group of pharmaceutical toxicologists and consultants investigating the carcinogenic potency and structure-activity relationships of N-nitrosamines. This is in response to the recent discovery of N-nitrosamines in marketed pharmaceuticals and the regulatory changes that have resulted. The working group is coordinated on an informal basis

Introduction to Lhasa Carcinogenicity Database For many years the Carcinogenic Potency Database (CPDB)1, created by Lois Gold and her team, was an important source of long-term carcinogenicity study data. However, as the database had stopped being updated from 2007, Lhasa moved to safeguard the data by providing ongoing access through a freely available interface; the Lhasa

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