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Manufacture Technology and Equipment, Small Molecules, Technology and Equipment, Advanced Medicine, Bioprocessing - Upstream & Downstream, Bioprocessing - Upstream & Downstream

Cell Science

I initially started out as a computer scientist, but I soon became intrigued by the emerging field of synthetic biology. People were talking about programming cells in a way analogous to programming computers. It sounded pretty exciting, so I switched fields and did a PhD in synthetic biology. I followed that with an MD, because I was interested in the clinical applications of the technology, and then, in 2010, I started my lab at MIT. We focus on the development of cell engineering tools for diagnostic and therapeutic applications, and we have been applying these technologies to enable on-demand biomanufacturing.

Moving from computer science to biology was a bit of a culture shock – after all, programming cells is much harder than programming computers! Synthetic biology is now in a stage that computing was in after transistors were invented – before we understood how to combine them in complex, scalable and robust systems. It took decades to develop design rules that enabled the development of modern computers, and learning how to program cells will require a similar effort. Just like computing power during the IT revolution, the core drivers of synthetic biology – the ability to synthesize or sequence DNA – are increasing at rates similar to, or greater than, Moore’s Law (which noted that the number of transistors per square inch on integrated computer circuits would double approximately every year). We now have an opportunity to establish the design rules for creating complex, scalable, and robust biological systems.

We envisaged a laptop-sized system incorporating a cell line that could produce several different biologics.
Biomedicines on demand

DARPA sees synthetic biology as a potentially transformative technology. A few years ago, Geoffrey Ling launched Bio-MOD, but he knew that the relevance of such technology would extend beyond the military, into humanitarian applications, or even space exploration. I felt there was a good fit between our cell programming activities and other MIT expertise – for example, the micro-reactors for biologics manufacturing developed by Rajeev Ram in the Electrical Engineering and Computer Science department – so we jointly applied for DARPA funding, together with other colleagues at MIT and collaborating institutions with other relevant technologies.

We have focused on upstream processing, since this is where synthetic biology is most relevant. Currently, biologics are made in huge vats using cells that can only make single products. By contrast, we envisaged a laptop-sized system incorporating a cell line that could produce several different biologics. To achieve this, we had to develop two fundamental technologies.

First, we had to develop a micro-bioreactor that could accommodate a high density culture of our cells. Rajeev invented impressive little devices for culturing micro-organisms and even CHO cells at densities that matched or exceeded those achievable in a conventional bioreactor. Rajeev’s system also allows us to dispense with batch manufacture – we rapidly flow the media in, optimize the conditions and collect the output as a continuous process. Rajeev has been great to work; I think he’s super-talented at making the portable devices necessary for medicine-on-demand applications.

Second, we had to develop cell lines that could produce any one of multiple drugs according to need. Currently, we are talking two or three products per cell line, but in the future it could be four or five. Basically, we program the cell with genetic circuits that allow us to modulate its gene expression – and therefore switch drug production on or off – according to components in the culture media (1). Applications include making small batches of combination therapies, such as anti-cancer immunotherapies, from a single cell line. It also raises the prospect of distributed biologics manufacturing. Highly centralized, capital-intensive manufacturing plants could be replaced by systems so small and flexible that anyone could have one. In fact, after we published the paper, we heard from people who were interested in making their own insulin! The system isn’t ready for that yet though – there are many technical challenges, not to mention legal and regulatory hurdles. However, there are some potential near-term applications; for example, the ability to manufacture small batches of drugs for preclinical testing without having to invest in large-scale process optimization. Our system can help with that, so it could turn out to be a useful research and discovery tool. It could also help to reduce the price of R&D – and ultimately the price of biologics, which many people would welcome.

We are currently scaling up our system in terms of the number of drugs that we can express from one cell and the diversity of molecules that this approach can accommodate. Some of the key questions we’ll be focusing on include how many therapeutic protein genes can you fit into a single cell? Does it make sense to make multiple different organisms for different sets of drugs? Is the upper limit 10 different drugs in a cell, or less? Also, are we working with the best organism? We chose yeast because it grows fast and gives high yields, but there are other possible hosts, and we are now testing alternatives. Hopefully it won’t be long before we demonstrate production of FDA-quality drugs from our system.

Timothy Lu is Associate Professor of Biological Engineering and Electrical Engineering and Computer Science, MIT.

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  1. B Jusiak et al., “Engineering synthetic gene circuits in living cells with CRISPR technology”, Trends Biotechnol., 34, 535-47 (2016). PMID: 26809780
About the Author
Timothy Lu

Timothy Lu is Associate Professor of Biological Engineering and Electrical Engineering and Computer Science, MIT.

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