Chartres cathedral 1194-1260 Biotechnology: Industry expectations and Technological Evolution Implications for the well-educated student. • Part 1: Industry context in Australia and industry requirements • Part 2: An evolutionary/generational definition of biotechnology that captures technological change Part 1 Australia: Industry context 2001 • • • • 190 core biotech companies 460 non-core/support companies 5,700 employees +46% fulltime equiv. employees 1999 to 2001 Source: E &Y, 2001 Australia: Industry context 2006 • • • • • 427 core biotech companies 625 medical device companies Biotech employment doubled 2005 to 2006 Now > 12,100 people Operating in diverse fields – Therapeutics, bioprospecting, livestock genetics, molecular biology, biosensors, diagnostics, plant biotechnology, process technology, vaccines Source:Hopper & Thorburn Innovation Dynamics, 2007 Key features of biotechnology • Trans-disciplinary • Rapidly evolving and emerging fields – Nanotech, proteomics, genomics, bioinformatics, PTGS • A very diverse industry • A large number of small companies Implications for teaching • How should we deliver our teaching, for what seems to be a moving target? – Content? – Teaching methods? • Are we delivering what industry needs? – Core content knowledge – Generic skills A Review of Biotechnology Education & Industry Needs in Australia: Funded by AUTC/DEST and Carrick Institute for Learning and Teaching in Higher Education What did we ask? Asked of industry • What 3 attributes / abilities do you look for in graduates when they commence employment with your company? ob Pr g/ cr it /w te ch ni ca ls ill in gn es s an d ki ll 30 * Attributes ty * Ho ne s Responses 35 to le ar n th in ki In ng te /c rp re er at so iv na ity ls ki lls /te am w or k M is ce lla ne Co ou m s m un ic at io Ex n sk pe ill rie s nc e/ tra ck re co rd Ac ad em ic re su lts In de pe nd en ce so lv in En th us ia sm ic Sc ie nt if Attributes looked for in graduates * 25 20 15 10 5 0 Asked of industry • What 3 areas of technical knowledge do you see as most important amongst your scientists? Technical Knowledge Tech. Knowledge Important in Scientists * 35 * * 30 Responses 25 20 15 10 5 0 o M ar ul c le og ol bi y O c er th m he try is n ei ot r P em ch try is O er th Im m gy lo o un d an ll e C e su it s re ltu cu rm fo in o Bi s ic at g lo io b ro ic M Area of Technical Knowledge y m eo ot r P s ic gu Re QA y/ r to la Asked of industry • List skills requirements most affected by these technological developments in your company. M c ol he ec m ul /ch Bi ar b em oi . nf iolo or g m y at Fe ic r Co O s M me ul tis nt'n Re mp the r u k i /e g lle ng ula ter Ti / ss d/x ./pr tor IT ue -di oc y/Q s e M Dru cu cip ss A l on l d t i oc g d ure ne ev. e / f c lo na v./p ell lex' ty h l Sa a a bi le nti rm olo s/ g a m bod . d y ar e ke y/im ve l En N ting mu . a n / vi ro not com 'y e n Di m ag me chn 'n n o n De o ta lo Au vel stic l Bi gy to op s/m ote m m at en ol/ ch io n ta pa M /ro l bi th as b ol s oti og sp cs y ec /H T tr om S et ry n ei Pr ot Responses Skills Requirements most Affected by Tech. Devts. 35 30 * 25 20 15 10 5 0 Skills at io n n or k ca t io m un ic Co m re t ri ev te n W ** In fo rit m un i om in g lv ** al In /A fo rm na at ly io si s n T R ec es hn ea ol rc og h y M et ho do lo gy IP Bu in Bi s. ot Is ec su h es in R eg Bi 's ot ec on h m an uf .& us e W ra lC So Te am le m Mean Response 4.5 O ob Pr Demand for generic and technical skills * 4 3.5 3 2.5 2 1.5 1 0.5 2002 2002 2003 2004 0 Skills Ranking of key skills by Universities & Industry M o le c u la r b io lo g y O t h e r c h e m is t ry P ro t e in c h e m is t ry Im m u n o lo g y C e ll a n d t is s u e c u lt u re M ic ro b io lo g y P ro t e o m ic s R e g u la t o ry / Q A U n ive rs it y In d u s t ry 1 2 3 * 11 7 5 * 3 * 15 Discordances marked with asterisks 1 2 3 4 5 6 7 8 Recommendations • Do not dilute the chemistry Recommendations • Strong industry demand for certain ‘generic attributes’: – Problem solving – Teamwork – Communication – Creativity – Enthusiasm Recommendations • Implications for pedagogy – More problem based learning ?? • Core knowledge? – More team based activities ? – More hands-on, task based application of core knowledge? The future • Students paying more • Changing student expectations (customers) • Changing course preferences • Will there be sufficient numbers of science grads to fuel the new economy? – 23% decline in science enrolments 1989-2002 • Will there be sufficient investment to sustain innovation in Australia? • Will there be investment in core training in fundamentals like chemistry? Part 2 Evolutionary/generational definition of biotechnology. Part 2 • A static definition: – Application of biological knowledge for generation of products that are or will be valued by society – Value is contestable and changes over time Part 2 • Value is contestable and changes over time – Stage of development of the society – Risks to which it is exposed • people give you different definitions Part 2 • Don’t know what biotechnology is. – Narrow definition • They take a lot for granted. – health/longevity • They don’t know he details of how their food is produced – Supermarket mentality/urbanisation Taking a lot for granted A Question • What was average life expectancy at birth in Western Europe in 1750? Answer • 33 years Why? • • • • • No vaccines No antisepsis No antibiotics No analgaesia No knowledge of germ theory The Plague Doctor, Venice, 17th Century Courtesy Omnia, Lido de Venezia Year ?? Year 1796 Definition of biotechnology • An evolutionary/generational definition is best. First generation • • • • • Plant breeding Collection of herbs for medicine Animal breeding Bread making Wine, beer, sake (Saccaromyces cerevisieae; Actinomyces, Leuconostoc) • Fermented food products – – – – Yoghurt Cheese Soy Chocolate (!) First generation Bacillus Hanseniaspora Pichia membranifasciens Microorganisms in fermentation and flavour formation of cocoa to make chocolate Saccharomyces cerevisiae First generation Microorganisms per gram during fermentation of cocoa to make chocolate First generation Yeast cells (dividing) Amarna 1550-1070 BC Courtesy Delwen Samuel, King’s College, London Pitted Starch granules, evidence of malting. Tomb, Deir el Medina Courtesy Delwen Samuel, King’s College, London Historical facts: Humans have always guided evolution of crops! •A very small sample of wild plants were chosen and domesticated •More than 10,000 years of genetic selection Historical facts …..cont • Crops strains and genes have moved around the globe for centuries • All crops we grow today were once wild plants but no crop would survive in the wild anymore (without human support) • They bear little physical resemblance to their wild ancestors Fig.1 Wild varieties of potato from the Americas Improving on crop plants Development of modern varieties – how was it done? • Hybridization • Disease resistance • Increased yield • Crosses with wild relations – Some do not breed true so it is necessary for farmers to repurchase seeds The products of these methods have led to crop characteristics (phenotypes) as different as Great Danes and Chihuahuas. Fig.2 Wild chili variety Fig. 3 Selected chili variety Modern methods of crop improvement: •Are relatively more precise and predictable •Transfer a few genes into crop plants in contrast to random shuffling of older approaches •Can determine exactly where the genes have been inserted (Polymerase chain reaction) •Can measure the effect on all proteins in the plant •Mass spectrometry •HPLC Benefits • Decreased pesticide usage • Decreased fuel consumption • Decreased crop losses to pests and disease – Papaya anecdote (Hawaii) • Increased nutrient efficiency – nitrogen fixing cereals – Vitamins • Increased crop yields. • • • • GM crops 220 million acres under GM crops in 2005 1/3 in developing countries In India and Australia , 70% reduction in organochlorine and organophosphorous pesticides Medical biotechnology • • • • • • • • Massive reduction in disease burden since 1945 Eradication of smallpox Eradication of polio in developed nations Whooping cough Diptheria Tetanus Cholera Perinatal morality Medical biotechnology • Vaccines • Clean water Milestones Ancient to modern biotechnology Jenner (1796) • Smallpox vaccination Semmelweis (1847) • Recognised cause of puerperal fever and post-natal death in maternity wards • Did not yet know about “germ” origin of disease John Snow (1854) • Showed the connection between contaminated water and cholera • Used a Voronoi diagram to pinpoint the culprit water pump – Application of maths to biology • The importance of a clean water supply Miescher (1871) • Isolated DNA from the nucleus of thymus cells Miescher (1871) • Isolated DNA from the nucleus of thymus cells • Died of tuberculosis, Aged 51 (possibly from unpasteurised milk) Koch (1878) • In 1878 Koch discovered that microbes cause wounds to go septic • Big breakthrough came when he decided to stain microbes with dye, enabling him to photograph them under a microscope. • Using this method he was able to prove that every disease was caused by a different germ. He identified the microbes that caused tuberculosis in 1882 and cholera in 1883. Pasteur (1885) • Rhabies vaccine • Pasteurisation Joseph Meister came to Pasteur after being bitten by a rabid dog. Pasteur treated him with a rabies vaccine, The rabies virus would not be identified for another half a century. Ehrlich (1891) • Paul Ehrlich proposes that antibodies are responsible for immunity. He shows that antibodies form against the plant toxins ricin and abrin. With Metchnikoff, Ehrlich is jointly awarded the Nobel Prize in Medicine or Physiology in 1908. Fleming (1928), Florey, Chain, Heatley (1940s) Everyone knows that Alexander Fleming discovered penicillin by accident in 1928. Penicillium notatum It was largely due to the technical ingenuity of one man that enough penicillin was produced for the first hospital tests. That man was Norman Heatley Do students know who this is? Watson, Crick, Franklin & Wilkins, 1953 Salk and Sabin,1955 http://www-micro.msb.le.ac.uk/tutorials/polio/ilung.mov Køhler and Milstein (1975) • Monoclonal antibody technology • Immortal cells producing a single antibody of defined specificity in unlimited amounts First monoclonal antibodies for diagnostics, 1982 Cohen and Boyer, 1973 • First recombinant DNA experiments Recombinant human insulin, 1982 • Human insulin produced in E.coli • Previously had been purified from pig pancreas Recombinant therapeutics since 1982 • Many since 1982 – Protropin (human growth hormone) 1985 – Combivax (Hep B vaccine) 1986 – Pulmozyme (CF treatment) 1993 – Rituximab 1997 – Herceptin 1998 • Several hundred in clinical trial Polymerase chain reaction (1983) Kari Mullis http://www.youtube.com/watch?v=IqgFyPdVc4Y • The combination of monoclonal antibody technology with human genome project • A new therapeutic drug discovery paradigm New drug development paradigm made possible by the Human Genome Project, for development of therapeutic monoclonal antibodies. Humanized Antibodies The biological age for therapeutics and diagnostics “Magic Bullets” •1980’s – much excitement and money invested •But, clinical trials failed (except for orthoclone)– much money lost •Because the MAbs were mouse-derived – immunogenic (Human Anti-Mouse Antibodies) -Eliminates therapeutic antibody from system -Effector functions less effective(eg. complement activation). •Genetically engineer to make the MAbs appear more human (humanisation) The Immune System •B-lymphocytes express antibody (Each cell specific) •Foreign antigen enters body (eg Bacteria or Virus) •Binds to specific B-cell, prompting maturation •B-cell produces large quantities of antibody •Antigen-Antibody binding triggers other components of immune system •Subsequent infection – faster clearance (immunity) eg Cancer Cells Producing Monoclonal Antibodies A mouse will recognise a human protein as foreign. Injecting human antigen will stimulate increased production of B-cells producing antibody against the antigen. B-cells can be immortalised by fusion with a myeloma cell and the specific hybridoma cell purified. Limitless supply of specific antibody ! Murine Chimeric (0% Human) (67% Human) Humanised Fully Human (90% Human) (100% Human) Chimeric Antibodies V C V Mouse Antibody Gene C Human Antibody Gene Clone human Constant region Clone mouse Variable region V C Ligate V C Express Allows specificity Allows effector functions Decreases HAMA but can get HACA Humanised Antibodies Allows specificity Allows effector functions Less immunogenic Fully Human Antibodies •Xenomouse (Abgenix) – entire Ab-gene repertoire in mouse replaced with the human equivalent •Mouse produces antibodies which are 100% human •Specificity easily achieved •Effector functions active •Not immunogenic •Fast and easy production Monoclonal Antibody based therapeutics PRODUCT DEVELOPER/ MARKETER APPROVAL DATE TYPE TARGET DISORDER Orthoclone OKT3 (muromonab-CD3) Ortho Biotech / Johnson & Johnson 1986 Murine CD3 antigen on T lymphocytes Acute transplant rejection ReoPro (abciximab) Centocor/ Eli Lilly & Co. 1994 Chimeric Clotting receptor Blood clots in cardiac procedures Rituxan (rituximab) DEC Pharmaceuticals/ Genentech/Roche 1997 Chimeric CD20 receptor on B lymphocytes Non-Hodgkin's lymphoma Zenapax (daclizumab) Protein Design Labs/Roche 1997 Humanized Interleukin-2 receptor on activated T-cells Acute rejection of transplanted kidneys Herceptin (trastuzumab) Genentech/Roche 1998 Humanized HER2 growth factor receptor Breast cancers Remicade (inflixibmab) Centocor/Schering-Plough 1998 Chimeric Tumor necrosis factor Rheumatoid arthritis and Crohn's disease Simulect (basiliximab) Novartis 1998 Chimeric Interleukin-2 receptor on activated T-cells Acute rejection of transplanted kidneys Synagis (palivizumab) Medlmmune 1998 Humanized F protein of respiratory syncytial virus RSV infection in children Mylotarg (gemtuzumab) Celltech/ Wyeth-Ayerst 2000 Humanized CD33 antigen on leukemia cells myeloid leukemia Campath (alemtuzumab) Millennium Pharmaceuticals/Schering AG 2001 Humanized CD52 antigen on B and T lymphocytes B cell chronic lymphocytic leukemia Success stories • Rituxan (Chimeric Mab) – Effective against refractory non- Hodgkin’s lymphoma – Well tolerated (few side effects) • Herceptin – Genotype dependant – metastatic breast cancer (Her-2 positive) Infectious disease therapeutics • Infantile RSV (respiratory syncitial virus) – Humanized MAb (Medi-493) • Medimmune • Hepatitis B – Human Mab (Ostavir) • Novartis/Protein Design Lab • HIV – Humanized Mab (Pro 542) • Progenics/Genzyme Infectious disease diagnostics • Shortage of positive control sera limits our ability to produce diagnostic tests – Particularly difficult to source early postinfection sera (IgM) • Need for reliable supply of control reagents for diagnostic tests Infectious disease diagnostics • Serum positive controls are difficult to source for: – Diseases of children – Bordatella pertussus (whooping cough) – Rare diseases – Rocky mountain spotted fever – Dangerous diseases – Dengue fever – West Nile fever – Q fever Infectious disease diagnostics • With humanized or chimeric antibodies it will be possible to have a reliable source of positive control reagents for these diseases. • Longer term therapeutic reagents for these diseases. Infectious disease diagnostics • Comparison of engineered antibody versus serum for Srub typhus test – Jones & Barnard, 2007 (in press) Cancer therapeutic • Characteristic surface antigens – CMRF 44 – CD 83 • Make humanised antibodies that bind to these Cancer therapeutic • Graft versus host disease – Haemopoietic stem cell graft – Aim: depletion of dendritic cells • Prostate cancer therapy – Purification of dendritic cells – Use the cells to treat prostate cancer Antibody formats natural and engineered Antibody formats natural and engineered • Shark single chain antibodies Chartres cathedral 1194-1260 • A transdisciplinary synthesis of – mathematical – technical – artistic skill • Renaissance grew out of a transdisciplinary synthesis of – mathematical – technical – artistic skill – for a social purpose Biotechnology is transdisciplinary • Need graduates who can: – have core technical skills • chemistry • mathematical skills – problem solving skills – can mediate a dialogue between disciplines and value systems to build a structure with a social purpose. • Paradoxically consistent with expressed demands of industry Thankyou