Woolly Mammoth Revival Project Pushed to 2030s Amid Scientific Challenges
Colossal Biosciences cites increased genetic editing requirements and reliance on AI for timeline shift.
The ambitious project to resurrect the woolly mammoth has encountered delays, with scientists at Colossal Biosciences now targeting the early 2030s for the revival of the ancient species. This revised timeline marks a shift from earlier predictions that suggested the creature could be brought back within the decade.
Colossal Biosciences, a Dallas-based company, is employing advanced gene-editing technology, including CRISPR, and artificial intelligence to achieve de-extinction. The process involves using DNA extracted from mammoth remains found in Siberia and editing the genome of an Asian elephant.
Initially, the company estimated that modifying approximately 60 genes within an elephant's DNA would be sufficient to create a mammoth embryo. However, recent research indicates that more than 150 genes will require editing. This increased complexity has necessitated a reassessment of the project's timeline.
"We are thinking it will be in the early 2030s," Colossal CEO Ben Lamm told TIME. He further clarified that while a specific date remains elusive, the target is not as early as 2030 nor as late as 2036.
The company has reported success in genetically engineering a family of 38 woolly mice, which were modified to exhibit the shaggy hair characteristic of mammoths. This achievement, while significant, differs from the complete de-extinction of a larger mammal.
Colossal Biosciences is also applying its de-extinction technologies to other species, including the dodo bird, the Tasmanian tiger, and the moa. The company's reliance on AI is crucial for processing vast amounts of genetic data and simulating complex biological processes required for these ambitious endeavors.
The project's extended timeline highlights the significant scientific and technological hurdles involved in de-extinction. Efforts to recreate extinct species require intricate genetic manipulation and a deep understanding of evolutionary biology, with AI playing an increasingly vital role in accelerating research and problem-solving.