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Billionaire Isak Andic died while hiking with son Jonathan in 2024

The son of Mango founder Isak Andic has been detained by police in Spain over an investigation into his billionaire father’s death during a mountain hike in 2024.

Jonathan Andic, who was the Spanish fashion retailer’s chief executive during an unsuccessful stint in the mid-2010s, was taken into custody on Tuesday, police in Catalonia confirmed.

He had already been placed under investigation in connection with the possible murder of his father, who plunged to his death in December 2024 when the two were hiking alone in the Catalan mountains.

Isak Andic, who was born in Turkey, was Mango’s non-executive chair and, according to Forbes, was one of Spain’s wealthiest people with a fortune of €4.5bn when he died at the age of 71.

Jonathan Andic and his two sisters own 95 per cent of Mango, with the remaining 5 per cent in the hands of Toni Ruiz, its chief executive. Jonathan has a seat on the company’s board but no executive role.

The entrepreneur founded the business that became Mango as a blouse importer in Catalonia in the 1970s. He turned it into a global empire with annual sales of €3.8bn in 2025, second in size in the Spanish fashion business only to Zara-owner Inditex.

The Andic family has consistently maintained that the 100 metre fall that led to Isak Andic’s death was accidental.

In a statement on Tuesday, the Andic family said: “Jonathan Andic has been requested to provide a statement relating to the accident of 14 December 2024. He continues to co-operate fully with judicial proceedings. This process remains under judicial secrecy, we have nothing further to say at this time.”

Drug discovery is one of the most expensive pursuits in modern industry. Finding a single viable molecule can take a decade and cost billions, and most candidates still don’t make it. A generation of AI startups has promised to fix that — most have made the problem less painful for researchers, who are already technically sophisticated enough to use the tools.

But SandboxAQ thinks the bottleneck isn’t the models. It’s the interface.

The company has teamed up with Anthropic to integrate its scientific AI models directly into Claude — putting powerful drug discovery and materials science tools behind a conversational interface that requires no specialized computing infrastructure to use.

Founded roughly five years ago as an Alphabet spinout, SandboxAQ counts Eric Schmidt, Google’s former CEO, as its chairman. The company, which has raised more than $950 million from investors, has built out a number of different business lines, including a cybersecurity business.

One of the more unique things SandboxAQ does, however, is produce large quantitative models, or LQMs. These proprietary models are “physics-grounded,” meaning they’re built on the rules of the physical world rather than patterns in text. They can run quantum chemistry calculations and simulate both molecular dynamics and microkinetics, the study of how chemical reactions unfold at the molecular level. That matters because it tells researchers how candidate molecules are likely to behave before anyone sets foot in a lab.

“Trained on real-world lab data and scientific equations, LQMs are AI models engineered for the quantitative economy, a $50+ trillion sector spanning biopharma, financial services, energy, and advanced materials,” the company said in a news release that strongly suggests Sandbox AQ isn’t building another chatbot or code assistant — it’s chasing the economy that AI is supposed to transform.

Chai Discovery and Isomorphic Labs — both well-funded bets on better models — have focused on the science. SandboxAQ is focused on who can actually use it.

“For the first time, we have a frontier [quantitative] model on a frontier LLM that someone can access in natural language,” Nadia Harhen, SandboxAQ’s general manager of AI simulation, told TechCrunch. Previously, users of SandboxAQ’s LQMs would have had to provide their own digital infrastructure to run the models.

SandboxAQ’s customers tend to be computational scientists, research scientists, or experimentalists. Generally, these people work at large pharmaceutical or industrial companies and are searching for new materials that can become marketable products.

“Our customers come to us because they’ve tried all the other software out there, and the complexity of their problem is such that it didn’t work or didn’t yield positive results for them when that translation went to take place in the real world,” said Harhen.