Next-gen Biotech Drives Equipment Advances

The future holds enormous opportunities for the development of new biotech-based devices, equipment, systems and applications.

Biotechnology is defined as biological techniques applied to research and product development. Much of that research is basic research and much of it is defined as enabling technologies with numerous applications in industry. Biotech has become the leading component in the life science industry, with biotech discoveries now driving development of new pharmaceuticals, agricultural products and processes, medical techniques and procedures, environmental technologies and biofuel products. In the latest Burrill annual report on the global life sciences industry, they rightly refer to biotech as the tail wagging the dog. The biotech industry has gone through a number of ups and downs over the past 30 years with all but two companies—Amgen and Genentech—consistently burning through their investors’ funds.

The turning point was the Human Genome Project (HGP) in the late-1990s and early-2000s that developed the sequencing, analysis, software and sample preparation technologies that have been essential in building the intellectual property of those start-up companies into the industrial drivers that they now are. Biotech companies like Genentech (now owned by pharma giant Roche), Gilead Sciences, Celgene and Amgen now dwarf traditional pharmaceutical companies (which until about five years ago were the corporate life science giants) in terms of overall corporate value.

The advances being made in biotech go far beyond just the drug discovery and development research performed in biopharmaceutical companies. Real-time information being gained from these research advances will allow people to monitor their changing biological states, allowing them to prevent diseases at far earlier stages.

Earlier this year, Illumina, San Diego, Calif., announced that its products could now sequence an individual human genome for less than $1,000—a breakthrough target that includes the cost of chemicals, preparation, labor and expensing the cost of the sequencer system. That cost compares to the $2.7 billion that the HGP needed to sequence one human genome in 2001 and the $350,000 estimated cost it had evolved to by 2008.

“Illumina’s HiSeq X Ten system should give us the ability to analyze complete genomic information from huge sample populations,” says Eric Lander, a professor of biology at MIT and director of the Broad Institute, Cambridge, Mass. “Over the next few years, we have the opportunity to learn as much about the genetics of human disease as we have learned in the history of medicine.” (Lander was a principal in the publicly funded group of the HGP, he was the first author listed in the article published in Nature).

The Illumina system has the capacity to provide tens of thousands of samples annually using a system that analyzes fluorescently labeled nucleotides enabled through faster chemistry and new optics. As a result, the system can process sequence flow cells 10 times faster than previous systems. While initial units of these systems are only being used in high-level research centers, like the Broad Institute, the company says that commercial units “do not look too far off, as costs continue to plummet.” The initial systems are being used to build genomic databases for use in medical research and healthcare applications.

The biotech lab

If you walk into a typical biotech lab, you probably won’t notice too many visual differences from any other type of generic research lab (assuming you don’t walk into the sequencing part of the lab). As noted in the chart on the next page, the top two items used in the modern biotech lab include chemicals and reagents (69%) and centrifuges (65%). Of course, those chemicals and reagents include the advanced kits with the IP developed over the past 10 years that enable biotech researchers to make their breakthrough discoveries. The other high-use devices—centrifuges, freezers and chillers, incubators and pure lab water systems—are used in the preparation procedures for processing biological samples (body fluids, environmental samples, potential drugs and other biological components).

Also noted in the biotech equipment used in the lab chart (prepared from reader survey data collected recently by the editors of Laboratory Equipment) is imaging systems and microscopes (selected by 47% of the readers). The technology in these systems has seen dramatic advances over the past several years, giving biotech researchers new bioscience information and capabilities that were previously unavailable.

PerkinElmer, Waltham, Mass., for example, recently announced it has partnered with Sofie Biosciences, Culver City, Calif., to develop and commercialize preclinical positron emission tomography (PET)–X-ray and 3-dimensional computed tomography (CT) imaging systems. PET imaging is a preclinical tool used to understand the biology of disease, biological impact of drugs and clinical translation, often on animal models. These benchtop imaging systems provide highly sensitive and quantitative biological assays for oncology, immunology, neurobiology cardiology and pharmacology applications. They are complementary to PerkinElmer’s lines of optical imaging, microCT and various imaging reagents and probes.

The two companies also announced the development of a new translational imaging system—the G8 PET/CT Small Animal Imaging System—which integrates PET and CT into an innovative benchtop system that enables preclinical workflows for biologists, biochemists and pharmacologists. PerkinElmer already markets its G4 multimodal PET/X-ray imaging system that surrounds test animals with panel detectors that allow researchers to image trace amounts of fluorescent probes. These high-sensitivity systems translate into a 10x smaller dose to the animal and researcher alike. PerkinElmer’s G8 multimodal PET/CT imaging system integrates PET with a high-quality, sub-min microCT scanner for producing quality images and quantitative data.

The integration of these new imaging systems into the modern biotech lab supports the development and implementation of modern translational research labs that bring the clinical research and medical lab to the bedside of patients, thus further accelerating the analysis, understanding and treatment of diseases.

A number of leading-edge biotech equipment systems rated low on their overall use in the modern biotech lab due mostly to the fact that they’re not yet widely used or that their costs (purchase and operating) are often beyond the range of many traditional labs. This includes lab-on-a chip systems (selected by only 9% of the survey reader respondents), X-ray systems (9%), stem cell systems (8%), biosensors (17%) and dynamic light scattering systems (10%). This does not imply that these systems are either not considered or unimportant. In fact, it’s just the opposite— they have substantial future technology growth rates. Meanwhile, researchers are making use of existing, established systems for their analysis and sample preparation work.

Biotech equipment features

The most important features of the equipment in a biotech lab, according to our recent Laboratory Equipment reader survey, include accuracy (selected by 73% of the readers), ease-of-use (61%) and costs (59% for operating and 58% for initial equipment purchase cost). The second tier of selection criteria includes sensitivity (50%), resolution (43%) and flexibility (35%). The third tier includes throughput and speed (28% for each), software (26%), training requirements (25%) and overall equipment size (24%). Solvent use, waste and energy efficiency/use are not considered important features (negative or positive) for these equipment selections.

These survey results are consistent with the results from similar surveys performed by the editors of Laboratory Equipment over the past four years, with the exception that in some sustainability-focused surveys, energy efficiency/use are ranked somewhat higher, but not in the leading position in these surveys either.

Computational accelerants

As in most research areas, the continuing improvements in computer processing power, lower cost storage capabilities and more efficient software systems have been critical and integral components in the overall advances seen in the development of biotech research systems.

Researchers at the Howard Hughes Medical Institute’s (HHMI) Janelia Farm Research Campus, Ashburn, Va., for example, have recently developed a new computational method to rapidly track the complex and data-rich 3-D movements of cells in fluorescence microscope images, providing an automated methodology that bypasses the time-consuming process of reconstructing an animal’s developmental building plan cell-by-cell.

“We wanted to reconstruct the elemental building plan of animals, tracking each cell from very early development until late stages, so that we know everything that has happened in terms of cell movement and cell division,” says Phillipp Keller, a group leader at Janelia. “In particular, we want to understand how the nervous system forms. Ultimately, we would like to collect the developmental history of every cell in the nervous system and link that information to the cell’s final function. For this purpose, we need to be able to follow individual cells on a large scale and over a long period of time.”

This tracking schema is data-intensive and complex because cells in a developing embryo have different shapes and behaviors and can be densely packed, making it difficult for a computer to identify and track individual cells. Variations in the microscope’s image quality further complicated the analyses. Keller addressed this problem by creating a cluster analysis routine that tracked the cells on a frame-by-frame basis. For more complex analyses, the computer system employed more compute-intensive techniques for evaluating images over several frames, both backward and forward.

Computational applications in biotech research are all about the management and analysis of large data sets. Even the tracking of samples can become challenging when the volume becomes massive. The Institutional Bioband of Lausanne (BIL), Switzerland, for example, was created to support clinical research, or more specifically, genomics research. After DNA sequencing of all local patient samples in the biobank, BIL aims to exploit the genomic and clinical data for specific research projects. This data will be used to better understand disease, better target individuals who respond to treatment (personalized medicine) and identify patients who consent to participate in future clinical trials. The BIL collection of more than 300,000 human samples is based on five years of preparatory work. BIL employed Micronic, Aston, Pa., 2-D-coded tubes for the long-term storage of patient blood, serum and plasma samples at -80 C. A unique laser-etched 2-D code on the bottom of each tube provides an easy unambiguous means of storing, scanning, identifying and correlating data from a database on each sample.

Emerging biotech opportunities

When asked in the Laboratory Equipment reader survey to identify the emerging biotech research opportunities that they expect to see or pursue over the next several years, researchers revealed a number of areas of current research studies:

• Exploration of the neuroelectronic interface, the mating of charge-guided neuronal patterning with the computer chip – MW, Oceanside, Calif.

• Greater information technology allowing real-time feedback in biological studies – JA, Carmel, Ind.

• Increased focus on biomarker research for the detection and identification of cancers and disease – TL, Los Angeles, Calif.

• Highly sensitive Tropinin assays, vitamin D assays and molecular technologies – PS, Stockton, Calif.

• Next-gen sequencing on laser-microdissected tissue specimens – JK, Buffalo, N.Y.

• Xenotransplantation – JS, Louisville, Ky.

• Rapid detection of target microorganisms in environmental samples – FS, Buffalo Grove, Ill.

• Much faster PATs (process analytical technologies), more automation and single-use technologies: all with faster speeds – AG, The Netherlands

• NMR of protein-ligand complexes – JN, Indianapolis, Ind.

• Bioengineered hyaluronic acid matrices – MF, Spartanburg, S.C.

• Expansion of bench work to the hospital bed (translational research) – NC, Costa Mesa, Calif.

• Nitrogen/protein analyzers – SP, Kansas City, Kan.

• Metabolic pathway flux and control – GH, Pullman, Wash.

• Microfluidics-based blood imaging and analysis – JS, Stony Brook, N.Y.

• High-throughput metabolomics – RI, Hershey, Pa.

• 3-D printed cells – JJ, Baltimore, Md.

The last item in this list involving 3-D printing reflects on a recent announcement by researchers at Drexel Univ., Philadelphia, and Tsinghua Univ., China, concerning their creation of a 3-D model of a cancerous tumor using a 3-D printer. The model comprises a 10 mm by 10 mm scaffold of fibrous proteins coated in cervical cancer cells. The model was made from gelatin, alginate and fibrin, recreating the extracellular matrix of a real-life cancer tumor. The coating was made from Hela cells—a unique “immortal” cell line derived from a cervical cancer patient in 1951. The creation of this 3-D-printed model eliminates the ethical and safety limitations of performing clinical studies on these cancer tumors in human patients, and allows research to be performed on a much wider scale, thereby allowing drugs to be tested in a more realistic 3-D environment.

Three-dimensional printing is a tool initially developed more than 30 years ago that has seen increased application growth in the past several years. In the medical arena, this has been seen in the creation of scaffolds onto which non-cancerous tissues can be grown on a patient or animal surrogate and then grafted onto the patient for reconstructive surgical procedures. Still in its infancy, these biotech structures can also be created for cardiovascular surgical applications and possibly even organ transplants.