bioinformatics beyond the information age

Coding agents have changed how we work as bioinformaticians. The change is recent enough that most published guidance is already out of date, and the tools are meaningfully different from six months ago.  The friction of writing and executing code is mostly gone. We now work most on things the AI agents can’t be trusted… Read More » Bioinformatics in the world of AI coding agents

We’ve said it before, and we’ll say it again: AI rewards preparation, not ambition. Teams that invest in data quality and experimental design will always outperform those who just dive headfirst into the latest technology. We know this because we are often called in to course-correct those who did not heed this advice. In this… Read More » AI in the Wild Part 1: AI Readiness and Preparation

AI is useful in drug discovery when it is paired with strong biology, clean data, and realistic goals. The fastest gains come from workflow acceleration, especially coding, documentation, and metadata capture. The biggest failures happen when teams force complex AI onto messy or undersized datasets. Diamond Age helps teams choose the simplest method that answers the scientific question and avoids…

Call it snark or pragmatism, but a recent BioBuzz panel, “Leveraging AI Across the BioPharma Value Chain,” brought something rare to the AI conversation: honesty. The panelists didn’t worship at the altar of algorithms. Instead, they asked smart questions. When does AI really add value? When is it just a high-tech answer in search of… Read More » You Don’t Need AI for That

At Precision Med TRI-CON, I joined a panel on “Omics, Data, and AI in Precision Medicine,” where we tackled a big, messy question: What’s keeping AI from delivering on its full potential in precision medicine?  Spoiler alert: it’s not the algorithms. It’s the data. Or more specifically, the glaring lack of clean, curated, context-rich datasets.… Read More » AI Isn’t the Problem. Your Data Is.

Challenge A pharmaceutical company faced a critical situation when they reported a seriousadverse event (SAE) for a patient enrolled in their clinical trial. Swift action was neededto respond to the FDA’s questions, safeguard patients, and prevent disruptions to thetrial. However, addressing FDA’s questions presented a formidable challenge because itrequired extensive, non-standard genomic analys…

Challenge A therapeutics company struggled to use public omics datasets to guide critical portfolio decisions, such as identifying patient population sizes for different targets, evaluating opportunities for indication expansion to determine where their therapy might be most effective, and selecting the most appropriate cell lines for in vitro or PDX experiments. The datasets were scattered… Read…

by Eleanor Howe and Michael DeRan After attending Cellarity’s medSCAI Symposium on single-cell research, AI, and data-driven drug discovery, we came away buzzing with inspiration over new possibilities for our clients at Diamond Age. The event was loaded with insights and tech designed to shake up bioinformatics and open real doors for biotechs looking to… Read More » Big Data Potential for Small…

You’ve got your samples ready, your experiment lined up, and funding secured. Everything looks set, so what could possibly go wrong? Well, plenty, if you haven’t involved your bioinformatics team when designing your experiment. I get it—bioinformaticians usually get called in at the final step. But here’s the thing: we’re your secret weapon for avoiding… Read More » Prevent Data Disasters and Bio…

Ever been to an event that shows just how unstoppable brilliant women are—even over Zoom? That’s exactly what happened at the recent Women in the Enterprise of Science and Technology (WEST) Career Possibilities Panel & Speed Networking event, where I had the pleasure of moderating. It was all about making bold moves and building valuable connections… Read More » Empowering Women in STEM

Lately, I’ve been reflecting on the rise of AI in the life sciences, especially after attending the International Conference on Intelligent Systems in Molecular Biology (ISMB). AI is a double-edged sword in our field; while it does hold promise for advancing the field, like automating data analysis and uncovering complex patterns in large datasets, it… Read More » AI in Life Sciences: A Roadmap f…

Bulk RNA-Seq uses short read sequencing to deliver a comprehensive snapshot of gene expression across the entire transcriptome, making it a powerful and versatile tool in drug development. This technology is widely used to facilitate the identification, validation, and optimization of new therapeutic strategies by providing detailed insights into gene expression profiles under various conditions.…

Challenge A large pharmaceutical company struggled with inefficiencies in their computational pipelines for high-throughput sequencing data, which took approximately 19 hours to process. This prolonged runtime reduced their bioinformatics operations’ efficiency and led to high compute resource costs. At the time of this engagement, Diamond Age (DA) had been providing bioinformatics solutions for …

By analyzing the gene expression profiles of individual cells within a population, single-cell RNA sequencing (scRNA-seq) helps us to understand heterogeneity within cell populations, discover rare and novel cell types, and identify cell states associated with various biological processes and diseases. These unique advantages of scRNA-seq relative to previous measures of gene expression allow us……

Challenge A biotechnology client focused on developing novel methods for gene therapy needed to ensure that their constructs were accurately being integrated into the correct location in the genome and not at off-target locations, a crucial factor for the safety and efficacy of gene therapies. The client was using an existing publicly-available bioinformatics pipeline that… Read More » Custom Pip…

Challenge A high-impact bioinformatics core team within a leading pharmaceutical company,tasked with supporting multiple drug development programs across a vast R&Ddepartment, found itself grappling with a substantial challenge. The high demand fortheir services had stretched resources to their limits, resulting in a burgeoning backlog,an overwhelmed team, and delays in delivering analysis result…