How Dotmatics aims to help reduce the drug discovery failure rate

It’s clear that drug discovery and development costs have rapidly increased in recent decades. That said, estimates vary widely. For example, a 2020 article in JAMA noted that estimates range from $314 million to $2.8 billion.

A high drug discovery failure rate exacerbates the problem. Part of the challenge of making such calculations is the difficulty in identifying precisely the data that went into them. Some estimates measure drug developers’ total cost of drug discovery and development over a given period and divide it by the number of drugs introduced to the market.

The downside to this method is that it doesn’t shed light on the cost of drug development failures.

Software takes aim at drug discovery inefficiencies

The R&D scientific software firm Dotmatics aims to help pharmaceutical companies reduce the failure rate of drug discovery. The company recently debuted Small Molecule Drug Discovery Solution, a software package with…

Read more
  • 0

Drug discovery isn’t rocket science. It’s harder.

Early in my career, my manager used the phrase in the above headline to highlight the difficulty inherent in drug discovery. Over the ensuing years, I have seen that statement repeatedly confirmed by the brutal attrition in the discovery and development of new drugs. There are so many variables that can kill a drug discovery project — ranging from target validation and hit generation to off-target effects and formulation challenges — and that’s before even entering the clinic, where a whole new set of attrition factors arise. The number of variables to be simultaneously optimized is immense. One is never quite sure if it is even possible to thread the needle and arrive at a global optimum. It is a testament to the grit and persistence of drug discovery scientists that we have found as many lifesaving drugs as we have.

As a multiparameter optimization problem, drug discovery is perhaps the most challenging example we face. But recent advances in computational power and…

Read more
  • 0

5 common data management problems affecting drug discovery

Image courtesy of Pexels

Ask a pharma researcher how well they’re able to leverage their organization’s medical imaging data, and you might hear a discouraging response. While most pharma companies have massive amounts of clinical and medical imaging data, often, most of the imaging data isn’t ready for modern research processes and infrastructure. This imaging data is an untapped asset — it’s disorganized, difficult or impossible to query, not normalized and in no way ready for machine learning and AI. The result is innovation is slowed.

Imaging data is a rich source of information that can hold the key to many discoveries, but it is complex to work with. Pharma companies need a sophisticated data management infrastructure to help manage this complexity and seek to scale up their research.

Here are five common data management problems to consider as your organization evaluates its path forward.

Read more
  • 0

Cutting through the noise of machine learning for drug discovery

While the topic of AI in drug discovery has received considerable attention in recent years, mature deployments of techniques such as machine learning in the industry remain rare. 

“The chemistry domain is qualitatively different from any other problem that machine learning has exhibited real success in,” said Jason Rolfe, CTO of Variational AI (Vancouver). 

For one thing, there is a relatively limited number of FDA-approved drugs. As of 2018, FDA said it had approved 19,000 prescription drugs. 

A dataset involving FDA-approved drugs that have been tested in humans would be orders of magnitude smaller than the sort of datasets that underlie Generative Pre-trained Transformer 3 (GPT-3), a language model from OpenAI, an AI research company co-founded by Elon Musk.   

Jason Rolfe

High-throughput screening can generate substantially larger datasets. The PubChem database, which NI…

Read more
  • 0

The top 5 drug discovery stories of 2021

Image courtesy of Pixabay

The pandemic continued to remake the pharma and biotech industry this past year. A handful of companies fared exceptionally well at commercializing COVID-19 therapies. This fact promises to lead to sizable shifts in the rankings of pharma leaders. These trends were not yet evident in our spring roundup of the 50 largest pharma companies, which drew revenue figures from the prior year. But in 2021, companies like Pfizer and Moderna sold tens of billions of dollars of COVID-19 vaccine alone. As a result of the ongoing pandemic, significant shifts are likely in 2022’s forthcoming ranking of pharma leaders.

Here, we provide an opportunity to review the 2021 pharma landscape, including stories that received the most attention on social media.

1. Pharma 50: The 50 largest pharmaceutical companies in the world

The top 50 largest pharmaceutical companies raked in $851 billion…

Read more
  • 0

Realizing the potential of flow chemistry in hit to leads

Flow chemistry image courtesy of Vernalis Research

Flow chemistry is a growing technology in the pharma industry, where it has proved itself invaluable, especially in the process development phase of drug discovery. However, the hit-to-lead generation phase of drug discovery has been slower to embrace these techniques. Nevertheless, the potential benefits are huge, particularly for rapid library generation and challenging chemistries that were previously hard to achieve by traditional batch methods. This article looks at how finding a groundbreaking flow chemistry application led to the wider adoption of flow chemistry in synthesis at a small pharma company.

The pharma industry frequently collaborates with CROs and smaller technology companies in the lead generation phase of drug discovery, adopting a medicinal chemistry approach to the development, synthesis and analysis of drug molecules and other bioactiv…

Read more
  • 0

Organ-chips could streamline drug development, but hurdles remain

Emulate Bio’s CHIP-S1

While organ-on-a-chip technology has evolved tremendously over the past 15 years, adoption of the technology remains at an early stage. But as organ-chip technology advances and the R&D costs for pharma companies continue to hover near unsustainable levels, organ-on-a-chip technology has the promise to address what cell biologist and bioengineer Donald Ingber called the “broken” drug-development model. 

One of the key challenges is the drug industry’s reliance on animal studies in preclinical research, Ingber said in an Emulate Bio virtual event. “There are ethical issues,” said Ingber, a member of the company’s board of directors. “But the real problem is that the results of these animal preclinical models often don’t predict clinical responses,” he added. 

Complicating matters further is the rise of biologics, which make up a sizable portion of the drug-development pi…

Read more
  • 0

ERS Genomics and ZeClinics team up on gene-edited zebrafish disease models

The zebrafish, commonly found in aquariums, is widely tapped in drug development to understand disease mechanisms.

The advent of CRISPR gene editing has given researchers more flexibility in developing disease models, thanks to its ability to create gene-edited zebrafish variants.

To that end, the privately-held company ZeClinics (Barcelona) is using CRISPR-based techniques to make unique zebrafish variants. The company recently announced a licensing agreement with privately-owned ERS Genomics (Dublin), which holds intellectual property related to the popular genome-editing method known as CRISPR-Cas9.

“By providing [ZeClinics] access to this foundational CRISPR/Cas9 intellectual property, ZeClinics is able to continue to provide valuable preclinical models and services for drug discovery and development,” said Eric Rhodes, CEO of ERS Genomics, in a statement.

In particular, the collaboration could…

Read more
  • 0