Biotechnology as a field
Biotechnology is a platform technology that different people define differently, from the broad OECD definition to the narrower ones of medicines regulators. The field has been mapped by colour, by species and by platform, its history runs from ancient fermentation to synthetic life, and its current era has its own vocabulary and technologies: the omics and synthetic biology, artificial intelligence, and biomanufacturing and the biofoundry. Harnessing it brings benefits as well as dangers, which the public needs to understand in order to trust it.
Definitions of biotechnology
Ten people asked what biotechnology means give ten different answers. Definitions vary with a person's background, academic or industrial for example, so how an individual defines biotechnology needs attention. Biotechnology is a platform technology applied so broadly, to medical, artisan and environmental applications, that some applications seem unusual and pigeonholing it to define it is difficult. Artisan biotechnology can be described as a skilled craftworker manufacturing a product from a biological raw material, environmental biotechnology as biotechnology applied in the environment to make it healthier, and medical biotechnology as biotechnology that improves the health of humans and animals. Biotechnology supports the pharmaceutical product lifecycle, for instance in nonclinical work using in silico, in vitro and animal testing methods. It interfaces with artificial intelligence where AI makes finding healthcare solutions easier and faster, and some of its applications might seem curious, such as transplanting one person's healthy gut microbiota, via their faeces, to help a person with unhealthy gut microbiota. The biotechnology used in pharmaceutical and medical device production is a small proportion of the biotechnology used on the planet, and people already use biotechnology without always realising it. Biotechnology might be animal- or non-animal-based.
The Organisation for Economic Co-operation and Development (OECD) gives a single definition of biotechnology: the application of science and technology to living organisms, as well as parts, products and models thereof, to alter living or nonliving materials for the production of knowledge, goods and services. The European Commission uses the OECD definition, which encompasses artisan, environmental and medical biotechnology, in a version adding that biotechnology can be used to manufacture bio-based products (biomanufacturing) and can be part of the solution to societal and environmental challenges such as climate mitigation and adaptation, access to and sustainable use of natural resources, restoring vital nature systems, food supply and security, and human health. The OECD definition has influenced the definitions of biotechnology in the USA over time; in 2025 the USA was an OECD member country, although this might change under the US administration of the time. Regulations and definitions change over time and regulatory harmonisation is constant, with the rest of the world often following in the footsteps of Europe or the USA.
In 1983, as genetic recombination emerged in industry, the FDA's working definition of biotechnology was the application of biological systems and organisms to technical and industrial processes. It was necessarily broad, taking in both the age-old techniques for making beer or yogurt and the most advanced uses of recombinant DNA technology, and applications from enzymes for laundry detergents and the selective breeding of plants and animals to the genetic engineering of bacteria to clean up oil spills. By then the US Office of Technology Assessment had found differing definitions of biotechnology from eight foreign countries and three international organisations. The FDA also held then that, as with any new technology, ethical issues are raised, and that genetic engineering and cloning awaken many primordial fears about the power of science. In 2017 the FDA published a 74-page document based on the challenges small and mid-sized businesses faced in navigating various industry regulations.
The OECD definition is broad compared with more specific medical biotechnology definitions. The EMA defines biotechnology as the use of living organisms to create or modify products, including medicines. The pharmaceutical and medical device industries' definitions of biotechnology were established to ensure consumer safety when medical biotechnology applications were developed. In the pharmaceutical and medical device industries, biotechnology uses biological systems and living organisms in research and development and production processes for product development, and biotechnologies include biologic and biosimilar pharmaceuticals, vaccines and advanced therapy medicinal products (ATMPs), including gene and cell therapies and tissue-engineered products. The EMA classifies many medical biotechnology products regulated in the pharmaceutical industry under biologics and biosimilars, ATMPs (equivalent to US cell and gene therapies) and herbal products. Many medical device diagnostic products make strong use of molecular biotechnology within in vitro diagnostic devices. By contrast, many non-biological medical devices might have control over the biological aspects of a patient without being obvious biotechnology products. A heart pacemaker, for example, is an electronic device that modifies a patient's heart rhythm to normalise it, so under the OECD definition a pacemaker is a biotechnology.
The pharmaceutical and medical device industries often produce biotechnology products at molecular to whole organ levels, while artisan and environmental biotechnologies often happen at cellular to microorganism levels, though molecular techniques might be used in them depending on the application. The OECD definition might help people connect what farmers produce, what craftspeople and food producers manufacture, and what is on supermarket shelves and in homes, most of it at cellular to whole organism levels rather than molecular levels. Biotechnology also fits the WHO's idea of One Health as an approach to designing and implementing programmes, policies, legislation and research in which multiple sectors communicate and work together to achieve better public health outcomes.
Biotechnology may be defined as the innovative and creative application of biological substances and processes to develop industrial-scale solutions to complex problems. Its advancements drive the pharmaceutical industry forward in its constant striving for safer and more effective therapies, and they also benefit the food, energy and healthcare industries. It has also been defined as the technique of using microorganisms, such as bacteria, to perform chemical processing, such as waste recycling, or to produce other materials such as beer and wine, cheese, antibiotics and, using genetic engineering, hormones and vaccines. Others define it as a field of science that uses living organisms and organic substances to create or modify environments, produce goods or improve human health. It can also be defined by the use of biological systems and living organisms in production processes, and it is commonly employed to make medical treatments using biomolecules and living cells. Broadly, it refers to the use of living systems and organisms, or their derivatives, to modify or produce products for humanity's benefit, a definition that encompasses both the recent growth in genomics, proteomics and bioinformatics and the advancements of ancient civilisations.
Classifying biotechnology
One scheme sorts biotechnology by colour: red for medical research, green for plant-based and agricultural work, blue for marine and ocean ecosystems, white for industrial and commercial production, yellow for food production, grey for bioremediation, brown for desert research, gold for bioinformatics and nanobiotechnology, violet for the ethical and legal issues, and dark for biological warfare. Others sort it by species, animal, plant or microbial, or by platform, in vitro, in vivo or in silico. Plant biotechnology is the use of tissue culture and genetic engineering techniques to produce genetically modified plants with new or improved desirable characteristics. In human health, green (agricultural) and red (pharmaceutical) plant biotechnology cross over, and plant biotechnology uses plants as bioreactors to produce bioactive phytochemicals with potential applications in the pharmaceutical industry. Science is too complex and diverse to be colour-coded: aspirin travels from green to red to white and yeast from green to yellow to white. Going back to the Greek roots, bios for life and techne for craft or skill, does not help either, because the term life is no longer binary and artificial intelligence has given craft or skill a whole new meaning.
A Venn diagram roughly outlining where artisan, environmental and medical biotechnologies meet places among its examples biologic originator and biosimilar medicines, cell and gene therapies and ATMPs, healthcare diagnosis and treatment, herbal products, food poisoning, the release of genetically modified organisms, bioweapons and warfare, veterinary work, air, eutrophication, desert, marine and freshwater environments, agriculture, composting, food production, fermentation, bioremediation and nutrition, at levels from molecular through organ to whole organism. The diagram comes from brainstorming, and there are many other examples of where biotechnologies might interface.
An artisan is a skilled craft worker who makes or creates material objects partly or entirely by hand, often with a guild qualification or with skills recognised in some other way, such as by reputation. Artisan products generally contain bio-based ingredients grown in agriculture: animal products such as red and white meat, seafood, poultry, hair, feathers, skin, gut, oil, eggs and dairy products such as butter, cheese, cream and milk, and non-animal products such as beans, cereal stalks, fruit, fungi, grains, nuts, reeds, seeds, vegetables and wood. Artisan products can include a fermentation step, as in cheese making, or not, as in weaving. Fermentation is used in artisan, environmental and medical biotechnology, biologic and biosimilar drug manufacture included, but each fermentation process is nuanced by its application. Many university courses with microbiology modules teach that biotechnology includes bread making, cheese making and brewing, while other courses, such as biomedical science, do not necessarily go into the details of environmental biotechnology.
The history of biotechnology
People harnessed living organisms for their benefit from ancient times, and biotechnologies have branched off since then as biotechnology innovations advanced. The term biotechnology was conceived in 1919 by Károly Ereky, a Hungarian agricultural engineer, whose vision encapsulated the potential power of living organisms leveraged for industrial purposes. In roughly 6000 BC the Sumerians and Babylonians fermented yeast to brew beer, a practice rooted in observation and tradition rather than scientific understanding, and fermentation is now commonly used by many pharmaceutical companies. From 4000 BC the Egyptians mummified their dead with natural preservatives such as natron, oils and resins, which helped dehydrate the body, and the natron created an environment hostile to microorganisms, most commonly bacteria. Mummification also inadvertently preserved ancient pathogens, which scientists can now examine with modern biotechnological tools. By 1000 BC the Chinese were brewing alcohol and using it in traditional medicine, for instance as an anaesthetic during surgery. Roman concrete hardened through a biotechnological process involving the microbial mediation of minerals, and the Pantheon and the Colosseum are examples of its resilience.
In the Middle Ages herbal remedies became prevalent, with healers and apothecaries cultivating medicinal gardens and preparing concoctions, balms and tinctures that often incorporated fermentation and distillation. Applying mouldy bread or decaying plant matter to wounds was later observed to improve them significantly: medieval practitioners were unknowingly harnessing the bacteria-inhibiting properties of mould, probably penicillin, a use that laid the foundation for the earliest antibiotics. In the 1800s Louis Pasteur's discoveries in germ theory revolutionised microbial biotechnology and led to techniques such as pasteurisation, important in food safety and disease prevention. In 1865 Gregor Mendel began the pea-plant experiments that led him to dominant and recessive traits and the laws of inheritance. In the early 20th century Walter Sutton and Theodor Boveri proposed the chromosome theory of inheritance. In 1928 Alexander Fleming discovered penicillin, the world's first antibiotic, when he noticed a mould inhibiting bacterial growth. In 1944 Oswald Avery, Colin MacLeod and Maclyn McCarty showed that DNA is the genetic material that carries hereditary information, and in 1953 James Watson and Francis Crick, using the X-ray diffraction data of Rosalind Franklin and Maurice Wilkins, proposed the double helix structure of DNA. In 1970 Hamilton Smith and Kent Wilcox discovered restriction enzymes, which cut DNA at specific sequences, a discovery that later won Smith a Nobel Prize. In 1973 Herbert Boyer and Stanley Cohen performed the first recombinant DNA experiment, transferring a gene from one bacterium to another on a plasmid vector, and the experiment laid the groundwork for genetic engineering. Kary Mullis invented the polymerase chain reaction, which revolutionised the way DNA is studied and manipulated.
In 2006 Andrew Fire and Craig Mello received the Nobel Prize in Physiology or Medicine for discovering RNA interference, a means of silencing gene expression with small RNA molecules. In 2008 J. Craig Venter and his team synthesised an artificial bacterial genome and transplanted it into a recipient cell, creating the first synthetic life form and sparking discussion of the possibilities and ethical implications of synthetic biology. The rapid development and potential applications of CRISPR-Cas9 genome editing stirred a global dialogue on the ethical and societal implications of genetic modification, especially in humans, and there was even talk of bringing back the woolly mammoth by cloning preserved thigh bones.
The omics and synthetic-biology era
In 2019, in the era of omics (genomics, transcriptomics, proteomics and metabolomics), the term biotechnology seemed to one writer inane and inadequate for what was going on in biomedical research. The latest trends in biomedical research translate into new trends in medical writing, so writers have to continuously hone their skills, broaden their vocabulary and expand their knowledge base. A glossary of the era defines:
- omics: a neologism for the constellation of an organism's omic information, which includes the genome itself (genomic), transcription products (transcriptomic), protein products (proteomic) and metabolic products (metabolomic)
- synthetic biology: an interdisciplinary branch of biology and engineering that combines disciplines such as biotechnology, evolutionary biology, molecular biology, systems biology, biophysics, computer engineering and genetic engineering
- in silico: performed on computer or via computer simulation, a phrase coined in 1989 as an allusion to in vivo, in vitro and in situ, which refer to experiments done in living organisms, outside living organisms and where they are found in nature
- do-it-yourself biology (DIYbio): a citizen-science movement that aims to find innovative solutions by studying life-sciences topics in self-made laboratories, such as those assembled in kitchens and garages, that are not ruled by the policies of a research or academic institution
- medical entomology: also known as public health entomology, the study of insects and arthropods that affect human health as disease vectors
Biology had come a long way since the start of the Human Genome Project: in 2018 an infant with a rare disease was admitted, diagnosed, treated and discharged within 36 hours after his whole genome was sequenced in a record 19.5 hours. Life runs not on software and hardware but on what has been called all-ware, which makes it highly resistant to human reprogramming, yet synthetic biology, combining biology and engineering, enables life to be hacked, redesigned and even created. With CRISPR/Cas9 technology, gene editing had by 2019 never been easier, cheaper and faster. Medicine benefits from synthetic biology, from finding cures for genetic diseases to regrowing or repairing damaged tissues and organs using 3D printers. On an industrial scale synthetic biology needs resources beyond test tubes, which is where biology meets artificial intelligence: biological experiments can be automated as gene editing becomes a digital rather than a laboratory activity, and in 2019 Swiss scientists created the first computer-generated genome of an organism, a bacterium created in silico. The DIYbio movement originated, like start-up tech companies, in laboratories set up in the garages and kitchens of biohackers and bio-innovators. Its activities range from home microbreweries, CRISPR-editing marijuana and culturing fluorescent bacteria for art to the more ominous threats of bioterrorism, and there are concerns about the lack of checks and balances and ethical considerations. Recent outbreaks of mosquito-borne diseases such as dengue, malaria, Zika and chikungunya had revived medical entomology by 2019, and gene-editing techniques were being explored to control, even wipe out, disease-carrying mosquito species without harming the benign types.
Artificial intelligence in biotechnology
Artificial intelligence was a newcomer to biotechnology in 2022, making it easier and faster to find new drug targets for diseases, detect diseases and harmful mutations, programme synthetic DNA and analyse DNA sequence data. The massive amount of raw data generated in omics medical research has to be understood for medical treatments to succeed, but Big Data has produced a bottleneck in which lots of data go unprocessed because omics data-processing technology needs to catch up. A 2015 estimate put the genomic data produced yearly at population scale at about 40 petabytes, and almost 900 megabytes are needed to store one human genome. Bioinformatics, also known as computational biology, merges biology, computer science and information technology to help process large data sets, and it has accelerated gene and protein sequencing, identification, prediction of function, understanding of complexity, structure and folding, and drug design and development, with AI helping to make significant advances.
Genomics is the study of the sequence and function of genes, and the human genome is a set of approximately 3 billion base pairs on 23 pairs of chromosomes, with differences between individuals called genetic variations. Each person's genome holds a vast amount of data that standard statistical tools cannot analyse. DeepVariant, a convolutional neural network, outperformed standard tools on variant-calling tasks, and PrimateAI, a convolutional neural network trained on data from 120,000 human samples, outperformed other variant pathogenicity prediction tools. Understanding non-coding genes remains an open challenge, and up to 11% of the causes of rare genetic disorders are estimated to be traceable to them. A deep neural network called SpliceAI was able to predict non-coding genetic variants. The Human Genome Project, launched on 1 October 1990, took 13 years and almost US$3 billion to map the human genome as a mosaic of sequences from 13 individuals, and in 2022 amendments were still being made to the reference sequence. The US$1000 genome was announced in 2014, and by 2022 a human genome could be sequenced for about US$600, with the US$100 genome not far behind because of advances in AI and computing. Future personalised medicine will consider a patient's genome to design tailored therapies, and AI will make genetic testing more accurate, cheaper and accessible. Researchers were already using AI to identify genes responsible for rare diseases in individual patients, to understand cancer genomics and to create new therapies.
Proteins are chains of amino acids that can be arranged in many ways in three-dimensional space, so studying protein folding is difficult, and it is called a grand challenge in biology. Understanding how a protein folds is crucial because the folding reveals its function. Scientists study folding with X-ray crystallography, an expensive, time-consuming and error-prone process, and determining a structure by reading the amino acid sequence was impossible until 2020. In December 2020 Google DeepMind introduced AlphaFold, a neural network model that accurately predicts how proteins fold, acclaimed as the solution to the 50-year-old protein-folding problem, and three months later DeepMind and the European Molecular Biology Laboratory-European Bioinformatics Institute (EMBL-EBI) launched the AlphaFold Protein Structure Database, from which scientists can download the shape of every protein in the human body and the proteins of 20 additional organisms. The database is expected to help find solutions to antibiotic resistance, microplastic pollution and climate change.
Drug discovery is an expensive, complex and uncertain process, and machine learning and deep learning can be used to discover and optimise therapeutic candidates faster. AI is also expected to cut the costs of drug discovery, and one market size analysis put its potential savings at US$70 billion by 2028. So in 2022 leading pharmaceutical companies were forging partnerships with AI start-ups and companies, and faster drug discovery will require more medical writers to help get approvals from regulatory agencies.
AI-driven innovation in biotechnology and medicine will continue to increase, but it faces challenges. One of the biggest is the lack of properly annotated, standardised and non-biased data sets. Without data there can be no use of AI, and in supervised learning human experts have to label the desired output for a set of input data. In 2022 there was more hype than reality around AI in the biotech industry and start-ups, and executives believed there was a gap between what AI can do and what people think it can do.
Biomanufacturing
Biomanufacturing, also known as bioproduction, is biotechnology used in production, and both terms are familiar to the pharmaceutical industry as well as to industrial biotechnology outside it. Support services such as biobanks and supply chains need an understanding of biotechnology too, because mechanical vibration and suboptimal temperatures in transport and storage can cause biotechnology product defects that are risky for patients and bad for company reputations.
In 2023 biomanufacturing was a recent entrant in serious policy debates. US Executive Order 14081, issued on 12 September 2022, thrust it onto centre stage, with reports due to the President on how biotechnology and biomanufacturing could further societal goals in health, climate change and energy, food and agricultural innovation, resilient supply chains and cross-cutting scientific advances. Korea's Ministry of Science and ICT then announced a National Synthetic Biology Initiative to enhance the country's capabilities in biomanufacturing, one of whose four goals is to transition 30% of the manufacturing industry to a bio-based industry within ten years. On 14 November 2022 EuropaBio, Europe's largest biotechnology industry group, announced a cross-sectoral Biomanufacturing Platform to strengthen the link between biotechnology and competitiveness, health and sustainability across Europe, with the mission to represent biomanufacturing at the highest policy levels in Europe.
As the scope of One Health expands, biomanufacturing has taken on new significance as a route to more sustainable manufacturing in the face of the current overwhelming reliance on fossil resources for fuel, energy and materials. Biomanufacturing is not new in human health, but for the industrial production of fuels, chemicals and materials its goal is the gradual replacement of reliance on fossil resources like oil and gas. Some of its solutions, it has been argued, could help consolidate a bioeconomy at a time when alternatives to oil-based production are urgently needed. Using renewable carbon to make molecules identical to the products of the petrochemicals industry, so-called drop-ins, should in theory reduce emissions, and much evidence seems to bear this out. Fossil-based thermoplastics are non-biodegradable over hundreds of years but fragment into microplastics and nanoplastics in the oceans, the destination of many millions of tonnes of them each year. Producing biodegradable plastics at a competitive scale to tackle plastics in the oceans has been a goal for several decades, and there are several candidate molecules but little market penetration.
Scaled-up manufacturing poses different challenges for biopharmaceuticals and for chemicals and materials. Pharmaceuticals are produced in comparatively much smaller volumes and have much higher added value than commodity chemicals, which makes small-scale production more easily profitable. Pharmaceuticals have a rigorous regulatory system, but the regulation of chemicals and materials is not trivial either. The sheer volume of a bio-based commodity chemical or bioplastic creates major roadblocks to scaled production. Fermentation processes for such products generally give low titres, which require expensive downstream processing to concentrate a dilute product, and they are generally much slower than petrochemical processes. Microbial manufacturing of commodity chemicals is also thwarted because they are highly reduced and non-natural compounds relative to carbohydrate feedstocks. A 2011 metabolic engineering process for 1,4-butanediol, a commodity chemical used in the annual manufacture of over 2.5 million tonnes of polymers, has been commercialised, but many more targets remain: the chemicals industry manufactures at least 70,000 different products, the most important and highest-volume of them from petrochemistry.
The biofoundry
One of the major challenges of bio-based production systems like fermentation is that the microorganisms used are not optimised for large-scale systems, and the most promising design tool to overcome it is the biofoundry. A biofoundry is a highly automated facility that uses laboratory robots programmed for specific tasks defined in a workflow, and it is a platform technology applicable across many of the sectors relevant to One Health. The biofoundry has been explored as a missing link in the design phase of biomanufacturing. The biofoundry automates the design–build–test–learn (DBTL) cycle, and standards, automation and machine learning are key to its success. As in modern manufacturing, the biofoundry, the site of design, can be totally separated from the site of manufacturing, typically the biorefinery, using data transfer to dematerialise the process. The DBTL cycle demands much work, time and cost, and much of it in synthetic biology is still semi-artisanal. So the biofoundry's overarching function is to accelerate and automate the cycle with increasing consistency and throughput while reducing labour and thus cost, and biofoundries mostly aim at streamlining the engineering of microbial chassis for chemical production. Huge advances in genome sequencing have facilitated high-throughput design and build, and advances in technologies such as microfluidics make it possible to automate the test phase as well. The bottleneck now lies in the learn phase, where machine learning holds out the hope of further accelerating the cycle. Integrating machine learning into the cycle could aid in developing accurate models for clinical studies and precision therapies, even leading to diagnostic and therapeutic microbes that identify diseases in situ and produce drugs in vivo based on the diagnoses. In the chemical and environmental fields, bacteria could similarly be developed to break down cellulosic biomass and ferment the sugars into products such as biofuels and bioplastics, a consolidated bioprocessing that has been a long time coming and that automation looks set to bring to reality.
The biofoundry could perhaps be the design platform to increase the number of candidate molecules for biodegradable plastics, though the bottleneck at testing and learning would remain, and machine learning and AI may have a role in identifying the candidates most effectively degraded under different conditions. Electronic databases have replaced paper sources such as the 1,262-page volume on the microbial transformation of non-steroid cyclic compounds that Klaus Kieslich published in 1976.
Quantitative structure–activity relationships (QSARs) may be the most useful predictive tools, and integrating them into biofoundry operations might provide predictive power. AI, machine-learning and deep-learning models, often using databases of QSARs, can now predict the biodegradability of organic chemicals and bio-based plastics, so it is speculated that they could be integrated into the automated biofoundry to predict the biodegradability of new candidate molecules for biodegradable plastics. In human and environmental health, QSARs could serve in in vitro and in silico toxicology testing before clinical trials of a putative drug molecule, in predicting oxidative stress in humans caused by organic chemicals and in predicting the environmental toxicity of pollutant chemicals. In drug design, virtual screening emerged as a powerful computational approach to screen large libraries of small molecules for new hits that can then be tested experimentally, on the principle that variations in structural properties cause different biological activities, and QSAR analysis is the most powerful virtual screening method for its high and fast throughput and good hit rate. Many constraints remain in drug design, and ensemble-based machine learning approaches have been used to overcome them and obtain reliable predictions. In 2023 the literature lacked a link between the goals of the DBTL cycle, especially its bottlenecked learn phase, and the goals of QSARs. As QSARs are mathematical models, integrating them into the software operations of biofoundries should in theory not be impossible.
A clear role for medical writers will be to delineate the changes to regulatory systems made necessary by technologies that generate candidate molecules faster and filter them through tools such as QSARs.
Benefits, dangers and public understanding
The adage that with great power comes great responsibility, which Hollywood has identified with biotechnology gone haywire as well as with superpowers, applies to biotechnology regardless of definition, colour, species or platform: harnessing it brings huge benefits as well as dangers. The human desire to harness life's tools to solve complex problems has been both a blessing and a curse: anyone working with monoclonal antibodies and other therapeutic biotechnology products is working with genetically modified organisms, and recent darker moments are reminders of the perils of unrestricted scientific exploration. Biotechnology is controversial, and one writer on biotechnology holds that it is more benign than it is given credit for, has the potential to make a positive difference in people's lives and should not be feared. The same writer holds that connections between biotechnology and its impact on everyday life can and should be drawn, while asking whether that is medical writing. Biotechnology often suffers from a bad reputation, which negative media stories about controversies involving biotech companies do not help, while many scientists believe AI could lead to a dystopian future, and both are likely to be difficult for the public to accept without effective communication.
The advances of biotechnology research depend on AI, and because of the field's complexity the research needs a significant amount of public trust, which requires that the public understand the benefits and risks of those advances. Medical writers are experts in conveying complex medical information in easy-to-understand language. Medical writers and communicators are key in demystifying biotechnology, and by writing and reporting the science accurately and comprehensibly they help keep it safe and honest. Medical writers have played a crucial role in biotechnology's development by critically articulating data about it, and they have helped advance the field and get drugs developed; their ability to communicate complex scientific information accessibly has been vital in bridging the gap between the scientific community and the public. One writer's definition calls biotechnology an intrinsic part of existence, woven into lives, society and the world, whose ongoing journey is about evolving the understanding of ethical practice as well as mastering life's mechanisms.