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The paradox of data in precision medicine
The path to faster breakthroughs in precision medicine begins with overcoming the complexities of multi-modal data. Discover how innovative solutions are enabling more personalised treatments.
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Machine learning
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The Pistoia Alliance: key findings on AI
Results from Pistoia Alliance’s Lab of the Future survey has shared important findings about the challenges life science companies face.
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Part two: the impact of poor data quality
In this four-part series, Dr Raminderpal Singh will discuss the challenges surrounding limited data quality, and some pragmatic solutions. In this second article, he discusses the problems that occur when using data of poor quality.
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Part one: an introduction to data quality
In this four-part series, Dr Singh will discuss the challenges surrounding limited data quality, and some pragmatic solutions. In this first article, the key attributes that define data quality and its requirement for data scientists are elucidated.
podcasts
Advanced techniques in toxicity testing
Tune in to this episode where we explore how innovative assays and human-relevant cell models are transforming toxicity screening in drug development.
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Assessing the risk of HCC with machine learning
A novel screening tool may increase the five-year survival rate of hepatocellular carcinoma patients to 90 percent.
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New 3D genomic profiling technique details PanINs
Researchers have developed a 3D approach to improve the characterisation of pancreatic intraepithelial neoplasias.
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Machine learning’s growing importance in researching cells
As we move towards more generalised AI models, neural networks and natural language interfaces, we’re starting to see machine learning take the place of higher order reasoning and data analysis “sense making.” Traditional scientific inquiry has typically been about asking specific questions of a specific model system under specific conditions.…
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Unlocking the potential of natural products in drug discovery
Natural products play an underappreciated role in drug discovery. Tandem mass spectrometry (MS/MS)-based metabolomics coupled with machine learning is allowing new, highly diverse molecules from natural products to be identified, revealing bioactive compounds and pinpointing promising drug targets. The additional dimension provided by trapped ion mobility (TIMS) enables researchers to…
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SARS-CoV-2 viral peptide fragments cause serious inflammatory response
In this Q&A, Dr Gerard Wong elucidates the inflammatory capacity of fragmented viral components from the perspective of supramolecular self-organisation.
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Reducing drug resistance in acute myeloid leukaemia patients
Researchers conducted a proteogenomic characterisation and found that drug exposure changes drug sensitivity.
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A new machine learning tool identifies drugs to minimise fibrosis
The computer model enables a better understanding of how drugs affect fibroblasts and finds a promising candidate to prevent heart scarring.
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New algorithm can predict when cancer will resist chemotherapy
The ML algorithm explores how genetic mutations collectively influence a tumour’s reaction to drugs impeding DNA replication.
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How AI is accelerating the future of precision medicine
Dr Ketan Patel, Clarivate, shares his insights about the use of Real-World Data and genomic biomarker data and discusses how researchers can use these to better detect and diagnose diseases.
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Unexpected patterns in DNA mutations identified
Disruptions in TP53 and RB1 are key influencers that cause changes in the risk of mutations across chromosomes.