Showing posts with label pharmaceutical. Show all posts
Showing posts with label pharmaceutical. Show all posts

Wednesday 3 October 2018

Pharmceutical Errors

Pharmceutical Errors are different from Medic ok p6 y yal Errors.
.
Manufacturing Errors
Compounding Errors 
Dispensing Error
Storage Errors
Clerical errors
Inventory errors
computer entry
Data entry in sheet errors
Pharmceutical Calculation Errors
Pharmaceutical Formulation Errors (Research & Development Errors)
Pharmaceutical Analysis Errors
Method of administration Errors
Drug Dose Titration Errors
Adverse Drug Reaction Reporting Errors (Pharmacovigilance Errors)
Drug Drug Interaction Reporting Errors
Ward Round Errors

Sunday 6 March 2016

Always think ... is it Medicinal or Pharmaceutical ?

I am strictly adamantly against about usage of terms like "medicinal or medical" in any Pharmacy sector, Creates unneccessary confusion : 
eg Medical research when actually its a pharmaceutical research
eg Medicinal Chemistry when actually its a Pharmaceutical Chemistry
eg Medical Store when actually its a Pharmacy
eg Medical Camp when actually its a Pharmacy Camp
eg Medical devices when actually its a Pharmaceutical device
eg Medical mnemonics when actually its a Pharmaceutical mnemonics(clinicaly oriented pharma mnemonics are different from industry oriented pharma mnemonics)

Actually Pharmacy is called by so many names :drug store/medical store/pharmacy

Friday 14 June 2013

Drug design

Drug design, sometimes referred to as rational drug design or more simply rational design, is the inventive process of finding new medications based on the knowledge of a biological target.[1] The drug is most commonly an organic small molecule that activates or inhibits the function of a biomolecule such as a protein, which in turn results in a therapeutic benefit to the patient. In the most basic sense, drug design involves the design of small molecules that are complementary in shape and charge to the biomolecular target with which they interact and therefore will bind to it. Drug design frequently but not necessarily relies on computer modeling techniques.[2] This type of modeling is often referred to as computer-aided drug design. Finally, drug design that relies on the knowledge of the three-dimensional structure of the biomolecular target is known as structure-based drug design.
The phrase "drug design" is to some extent a misnomer. What is really meant by drug design is ligand design (i.e., design of a small molecule that will bind tightly to its target).[3] Although modeling techniques for prediction of binding affinity are reasonably successful, there are many other properties, such as bioavailability, metabolic half-life, lack of side effects, etc., that first must be optimized before a ligand can become a safe and efficacious drug. These other characteristics are often difficult to optimize using rational drug design techniques.


Background

Typically a drug target is a key molecule involved in a particular metabolic or signaling pathway that is specific to a disease condition or pathology or to the infectivity or survival of a microbial pathogen. Some approaches attempt to inhibit the functioning of the pathway in the diseased state by causing a key molecule to stop functioning. Drugs may be designed that bind to the active region and inhibit this key molecule. Another approach may be to enhance the normal pathway by promoting specific molecules in the normal pathways that may have been affected in the diseased state. In addition, these drugs should also be designed so as not to affect any other important "off-target" molecules or antitargets that may be similar in appearance to the target molecule, since drug interactions with off-target molecules may lead to undesirable side effects. Sequence homology is often used to identify such risks.
Most commonly, drugs are organic small molecules produced through chemical synthesis, but biopolymer-based drugs (also known as biologics) produced through biological processes are becoming increasingly more common. In addition, mRNA-based gene silencing technologies may have therapeutic applications.

Types


Flow charts of two strategies of structure-based drug design
There are two major types of drug design. The first is referred to as ligand-based drug design and the second, structure-based drug design.

Ligand-based

Ligand-based drug design (or indirect drug design) relies on knowledge of other molecules that bind to the biological target of interest. These other molecules may be used to derive a pharmacophore model that defines the minimum necessary structural characteristics a molecule must possess in order to bind to the target.[4] In other words, a model of the biological target may be built based on the knowledge of what binds to it, and this model in turn may be used to design new molecular entities that interact with the target. Alternatively, a quantitative structure-activity relationship (QSAR), in which a correlation between calculated properties of molecules and their experimentally determined biological activity, may be derived. These QSAR relationships in turn may be used to predict the activity of new analogs.

Structure-based

Structure-based drug design (or direct drug design) relies on knowledge of the three dimensional structure of the biological target obtained through methods such as x-ray crystallography or NMR spectroscopy.[5] If an experimental structure of a target is not available, it may be possible to create a homology model of the target based on the experimental structure of a related protein. Using the structure of the biological target, candidate drugs that are predicted to bind with high affinity and selectivity to the target may be designed using interactive graphics and the intuition of a medicinal chemist. Alternatively various automated computational procedures may be used to suggest new drug candidates.
As experimental methods such as X-ray crystallography and NMR develop, the amount of information concerning 3D structures of biomolecular targets has increased dramatically. In parallel, information about the structural dynamics and electronic properties about ligands has also increased. This has encouraged the rapid development of the structure-based drug design. Current methods for structure-based drug design can be divided roughly into two categories. The first category is about “finding” ligands for a given receptor, which is usually referred as database searching. In this case, a large number of potential ligand molecules are screened to find those fitting the binding pocket of the receptor. This method is usually referred as ligand-based drug design. The key advantage of database searching is that it saves synthetic effort to obtain new lead compounds. Another category of structure-based drug design methods is about “building” ligands, which is usually referred as receptor-based drug design. In this case, ligand molecules are built up within the constraints of the binding pocket by assembling small pieces in a stepwise manner. These pieces can be either individual atoms or molecular fragments. The key advantage of such a method is that novel structures, not contained in any database, can be suggested.[6][7][8]

Active site identification

Active site identification is the first step in this program. It analyzes the protein to find the binding pocket, derives key interaction sites within the binding pocket, and then prepares the necessary data for Ligand fragment link. The basic inputs for this step are the 3D structure of the protein and a pre-docked ligand in PDB format, as well as their atomic properties. Both ligand and protein atoms need to be classified and their atomic properties should be defined, basically, into four atomic types:
  • hydrophobic atom: All carbons in hydrocarbon chains or in aromatic groups.
  • H-bond donor: Oxygen and nitrogen atoms bonded to hydrogen atom(s).
  • H-bond acceptor: Oxygen and sp2 or sp hybridized nitrogen atoms with lone electron pair(s).
  • Polar atom: Oxygen and nitrogen atoms that are neither H-bond donor nor H-bond acceptor, sulfur, phosphorus, halogen, metal, and carbon atoms bonded to hetero-atom(s).
The space inside the ligand binding region would be studied with virtual probe atoms of the four types above so the chemical environment of all spots in the ligand binding region can be known. Hence we are clear what kind of chemical fragments can be put into their corresponding spots in the ligand binding region of the receptor.

Ligand fragment link


Flow chart for structure-based drug design
When we want to plant “seeds” into different regions defined by the previous section, we need a fragments database to choose fragments from. The term “fragment” is used here to describe the building blocks used in the construction process. The rationale of this algorithm lies in the fact that organic structures can be decomposed into basic chemical fragments. Although the diversity of organic structures is infinite, the number of basic fragments is rather limited.
Before the first fragment, i.e. the seed, is put into the binding pocket, and other fragments can be added one by one, it is useful to identify potential problems. First, the possibility for the fragment combinations is huge. A small perturbation of the previous fragment conformation would cause great difference in the following construction process. At the same time, in order to find the lowest binding energy on the Potential energy surface (PES) between planted fragments and receptor pocket, the scoring function calculation would be done for every step of conformation change of the fragments derived from every type of possible fragments combination. Since this requires a large amount of computation, using different tricks may use less computing power and let the program work more efficiently. When a ligand is inserted into the pocket site of a receptor, groups on the ligand that bind tightly with the receptor should have the highest priority in finding their lowest-energy conformation. This allows us to put several seeds into the program at the same time and optimize the conformation of those seeds that form significant interactions with the receptor, and then connect those seeds into a continuous ligand in a manner that make the rest of the ligand have the lowest energy. The pre-placed seeds ensure high binding affinity and their optimal conformation determines the manner in which the ligand will be built, thus determining the overall structure of the final ligand. This strategy efficiently reduces the calculation burden for fragment construction. On the other hand, it reduces the possibility of the combination of fragments, which reduces the number of possible ligands that can be derived from the program. The two strategies above are widely used in most structure-based drug design programs. They are described as “Grow” and “Link”. The two strategies are always combined in order to make the construction result more reliable.[6][7][9]

Scoring method

Structure-based drug design attempts to use the structure of proteins as a basis for designing new ligands by applying accepted principles of molecular recognition. The basic assumption underlying structure-based drug design is that a good ligand molecule should bind tightly to its target. Thus, one of the most important principles for designing or obtaining potential new ligands is to predict the binding affinity of a certain ligand to its target and use it as a criterion for selection.
One early method was developed by Böhm[10] to develop a general-purposed empirical scoring function in order to describe the binding energy. The following “Master Equation” was derived:
\begin{array}{lll}\Delta G_{\text{bind}} = -RT \ln K_{\text{d}}\\[1.3ex]
K_{\text{d}} = \dfrac{[\text{Receptor}][\text{Acceptor}]}{[\text{Complex}]}\\[1.3ex]

\Delta G_{\text{bind}} = \Delta G_{\text{desolvation}} + \Delta G_{\text{motion}} + \Delta G_{\text{configuration}} + \Delta G_{\text{interaction}}\end{array}
where:
  • desolvation – enthalpic penalty for removing the ligand from solvent
  • motion – entropic penalty for reducing the degrees of freedom when a ligand binds to its receptor
  • configuration – conformational strain energy required to put the ligand in its "active" conformation
  • interaction – enthalpic gain for "resolvating" the ligand with its receptor
The basic idea is that the overall binding free energy can be decomposed into independent components that are known to be important for the binding process. Each component reflects a certain kind of free energy alteration during the binding process between a ligand and its target receptor. The Master Equation is the linear combination of these components. According to Gibbs free energy equation, the relation between dissociation equilibrium constant, Kd, and the components of free energy was built.
Various computational methods are used to estimate each of the components of the master equation. For example, the change in polar surface area upon ligand binding can be used to estimate the desolvation energy. The number of rotatable bonds frozen upon ligand binding is proportional to the motion term. The configurational or strain energy can be estimated using molecular mechanics calculations. Finally the interaction energy can be estimated using methods such as the change in non polar surface, statistically derived potentials of mean force, the number of hydrogen bonds formed, etc. In practice, the components of the master equation are fit to experimental data using multiple linear regression. This can be done with a diverse training set including many types of ligands and receptors to produce a less accurate but more general "global" model or a more restricted set of ligands and receptors to produce a more accurate but less general "local" model.[11][12][13]

Rational drug discovery

In contrast to traditional methods of drug discovery, which rely on trial-and-error testing of chemical substances on cultured cells or animals, and matching the apparent effects to treatments, rational drug design begins with a hypothesis that modulation of a specific biological target may have therapeutic value. In order for a biomolecule to be selected as a drug target, two essential pieces of information are required. The first is evidence that modulation of the target will have therapeutic value. This knowledge may come from, for example, disease linkage studies that show an association between mutations in the biological target and certain disease states. The second is that the target is "drugable". This means that it is capable of binding to a small molecule and that its activity can be modulated by the small molecule.
Once a suitable target has been identified, the target is normally cloned and expressed. The expressed target is then used to establish a screening assay. In addition, the three-dimensional structure of the target may be determined.
The search for small molecules that bind to the target is begun by screening libraries of potential drug compounds. This may be done by using the screening assay (a "wet screen"). In addition, if the structure of the target is available, a virtual screen may be performed of candidate drugs. Ideally the candidate drug compounds should be "drug-like", that is they should possess properties that are predicted to lead to oral bioavailability, adequate chemical and metabolic stability, and minimal toxic effects. Several methods are available to estimate druglikeness such as Lipinski's Rule of Five and a range of scoring methods such as Lipophilic efficiency. Several methods for predicting drug metabolism have been proposed in the scientific literature, and a recent example is SPORCalc.[14] Due to the complexity of the drug design process, two terms of interest are still serendipity and bounded rationality. Those challenges are caused by the large chemical space describing potential new drugs without side-effects.

Computer-aided drug design

Computer-aided drug design uses computational chemistry to discover, enhance, or study drugs and related biologically active molecules. The most fundamental goal is to predict whether a given molecule will bind to a target and if so how strongly. Molecular mechanics or molecular dynamics are most often used to predict the conformation of the small molecule and to model conformational changes in the biological target that may occur when the small molecule binds to it. Semi-empirical, ab initio quantum chemistry methods, or density functional theory are often used to provide optimized parameters for the molecular mechanics calculations and also provide an estimate of the electronic properties (electrostatic potential, polarizability, etc.) of the drug candidate that will influence binding affinity.
Molecular mechanics methods may also be used to provide semi-quantitative prediction of the binding affinity. Also, knowledge-based scoring function may be used to provide binding affinity estimates. These methods use linear regression, machine learning, neural nets or other statistical techniques to derive predictive binding affinity equations by fitting experimental affinities to computationally derived interaction energies between the small molecule and the target.[15][16]
Ideally the computational method should be able to predict affinity before a compound is synthesized and hence in theory only one compound needs to be synthesized. The reality however is that present computational methods are imperfect and provide at best only qualitatively accurate estimates of affinity. Therefore in practice it still takes several iterations of design, synthesis, and testing before an optimal molecule is discovered. On the other hand, computational methods have accelerated discovery by reducing the number of iterations required and in addition have often provided more novel small molecule structures.
Drug design with the help of computers may be used at any of the following stages of drug discovery:
  1. hit identification using virtual screening (structure- or ligand-based design)
  2. hit-to-lead optimization of affinity and selectivity (structure-based design, QSAR, etc.)
  3. lead optimization optimization of other pharmaceutical properties while maintaining affinity
Flowchart of a common Clustering Analysis for Structure-Based Drug Design
Flowchart of a Usual Clustering Analysis for Structure-Based Drug Design
In order to overcome the insufficient prediction of binding affinity calculated by recent scoring functions, the protein-ligand interaction and compound 3D structure information are used to analysis. For structure-based drug design, several post-screening analysis focusing on protein-ligand interaction has been developed for improving enrichment and effectively mining potential candidates:
  • Consensus scoring[17][18]
    • Selecting candidates by voting of multiple scoring functions
    • May lose the relationship between protein-ligand structural information and scoring criterion
  • Geometric analysis
    • Comparing protein-ligand interactions by visually inspecting individual structures
    • Becoming intractable when the number of complexes to be analyzed increasing
  • Cluster analysis[19][20]
    • Represent and cluster candidates according to protein-ligand 3D information
    • Needs meaningful representation of protein-ligand interactions.

Examples

A particular example of rational drug design involves the use of three-dimensional information about biomolecules obtained from such techniques as X-ray crystallography and NMR spectroscopy. Computer-aided drug design in particular becomes much more tractable when there is a high-resolution structure of a target protein bound to a potent ligand. This approach to drug discovery is sometimes referred to as structure-based drug design. The first unequivocal example of the application of structure-based drug design leading to an approved drug is the carbonic anhydrase inhibitor dorzolamide, which was approved in 1995.[21][22]
Another important case study in rational drug design is imatinib, a tyrosine kinase inhibitor designed specifically for the bcr-abl fusion protein that is characteristic for Philadelphia chromosome-positive leukemias (chronic myelogenous leukemia and occasionally acute lymphocytic leukemia). Imatinib is substantially different from previous drugs for cancer, as most agents of chemotherapy simply target rapidly dividing cells, not differentiating between cancer cells and other tissues.
Additional examples include:
Case studies

GENERIC BRANDS

Generic brands of consumer products (often supermarket goods) are distinguished by the absence of a brand name. It is often inaccurate to describe these products as "lacking a brand name", as they usually are branded, albeit with either the brand of the store in which they are sold or a lesser-known brand name which may not be aggressively advertised to the public.[citation needed] They are identified more by product characteristics.
They may be manufactured by less prominent companies, or manufactured on the same production line as a 'named' brand. Generic brands are usually priced below those products sold by supermarkets under their own brand (frequently referred to as "store brands" or "own brands"). Generally they imitate these more expensive brands, competing on price. Generic brand products are often of equal quality as a branded product; however, the quality may change suddenly in either direction with no change in the packaging if the supplier for the product changes.

Comparison with store brands

At their initial introduction, generics were packaged in mostly white packaging with black lettering. Today, such stark package design is rarely used. Lower priced products today usually bear the name of the store or supermarket where it is sold, or the name of the distribution company that supplies that store. A variation on this that is common in the United States is private labeling: brand names owned by the store that sells the product, that are not the same as the name of the store. For example, supermarket chain Safeway, Inc. sells dairy products under the Lucerne brand, while the Kroger's line of supermarkets sells products under several names, ranging from the top quality Private Selection down to the budget-driven line Kroger Value.
Membership-based "warehouse club" stores have begun their own contract-packed brands. The Wal-Mart owned Sam's Club sells products under the name Member's Mark, Costco sells products under the name Kirkland Signature (a reference to former corporate home office location, Kirkland, Washington), and BJ's Wholesale Club sells products branded Berkley & Jensen (a store self-reference - "B & J").
'Generic branded food', as well as being cheaper than branded food products, may be a healthier alternative with independent research finding supermarket own-brand cereals containing less salt, and saturated fat than the branded equivalent.[1] In addition to price and nutrition, evidence suggests that quality is equal to, if not better than established brands and in the 2007 Whisky Bible several supermarket single malts were rated higher than top-brand distilleries with Tesco the highest rating own-brand.[2]

Premium and value generic brands

Rather than offering a single own-brand alternative, supermarkets have in recent years introduced 'premium' and[3] 'value' ranges offering varying quality and price. Some supermarkets advertise the quality of their premium own-brands for example Sainsbury's television commercial featuring celebrity chef Jamie Oliver.[4] Value supermarket brands are sold at considerably less than known brands, sometimes even below cost price, to entice the shopper into the store.[5] Despite perceived lower quality, supermarket own-brands continue to sell and a trading standards investigation found that there was little nutritional or taste difference between value and regular products.[6]

Generic drugs

When patent protection expires on a drug, a bioequivalent version may be sold as a "generic" version of the brand name drug, typically at a significant discount below the brand name. The utility of these products is considered to be the same as that of the original brand name.

Genericide

When a brand name is associated with every manufacturer’s product in the category it is said to have undergone Genericide. These brand names are still legally protected, but from the point of view of the consumer, the name is synonymous with the product. Some examples of Genericide include Band-aid, Aspirin and Dry Ice. [7]

Trends

Due to the lack of promotional effort, generic brands are priced lower than branded products.[8] They thus have a low "brand tax".[9] They are preferred by customers for whom price or value-for-money is the priority.
Cost-conscious consumers may find the tax to be paid for a brand or slight variation in quality unjustified, causing the brand item to have lower value-for-money. They may tend to pick cheaper substitute when they are nearby. The same consumers, however, may be willing to pay brand tax for a distinct category of products about which they are particular.
Generic products are generally more popular in recessionary times, when consumers' purchasing power is lower, putting them on the lookout for value-for-money products. Generic brands are more readily available for goods such as aluminium foil, CD/DVD, hand tools, paper products and small appliances.[10]

Issues

Consumer perceptions about generic brands differ widely. While purchasing generic drugs, there may be a perceived risk of the effectiveness and safety of the drug.
A generic brand skin care product may also have a consumer unsure about its ‘health and safety’ quotient. This implies that there are certain product categories more aligned to generic brands. Examples include over the counter medications, cereal and gasoline among others. [11]
Some generic products may try to leverage their already existing cost advantage (due to lack of promotional effort) further by using inferior ingredients for production. This can damage the reputation and lead to customers avoiding future purchase. Prevalence of such acts necessitates the customer crosschecking the crimp for list of ingredients and verifying that it is comparable to a name-brand.
Since customers may be unwilling to expend to extra effort required for price comparison or ingredient list matching, it is a good idea to buy generic brands for products with fewer ingredients. Eggs, fruits and vegetables are an easy choice.
Due to cultivation of a name brand mindset, customers might believe that a name branded product (say, cereal) tastes better than a generic one. In many cases, this may not be true. Misconceptions can be clarified by a blind test or by storing the product in clear glass containers.[

GENERIC DRUGS

A generic drug (generic drugs, short: generics) is a drug defined as "a drug product that is comparable to brand/reference listed drug product in dosage form, strength, route of administration, quality and performance characteristics, and intended use."[1] It has also been defined as a term referring to any drug marketed under its chemical name without advertising.[2] [3]
Although they may not be associated with a particular company, generic drugs are subject to the regulations of the governments of countries where they are dispensed. Generic drugs are labeled with the name of the manufacturer and the adopted name (nonproprietary name) of the drug.
A generic drug must contain the same active ingredients as the original formulation. According to the U.S. Food and Drug Administration (FDA), generic drugs are identical or within an acceptable bioequivalent range to the brand-name counterpart with respect to pharmacokinetic and pharmacodynamic properties. By extension, therefore, generics are considered (by the FDA) identical in dose, strength, route of administration, safety, efficacy, and intended use.[4] The FDA's use of the word "identical" is very much a legal interpretation, and is not literal. In most cases, generic products are available once the patent protections afforded to the original developer have expired. When generic products become available, the market competition often leads to substantially lower prices for both the original brand name product and the generic forms. The time it takes a generic drug to appear on the market varies. In the US, drug patents give 20 years of protection.[5]
Prescriptions may be issued for drugs specifying only the chemical name, rather than a manufacturer's name; such a prescription can be filled with a drug of any brand meeting the specification. For example, a prescription for lansoprazole can be filled with generic lansoprazole, Prevacid, Helicid, Zoton, Inhibitol, or Monolitum.
A generic drug of biological type (e.g. monoclonal antibodies), is different to chemical drugs because of its biological nature and it is regulated under extended set of rules for it; see Biosimilars.

Nomenclature

See also: Drug nomenclature
Generic drug names are constructed using standardized affixes that separate the drugs between and within classes and suggest the action of the drug.

Economics

Generic drugs are usually sold for significantly lower prices than their branded equivalents. One reason for the relatively low price of generic medicines is that competition increases among producers when drugs no longer are protected by patents. Companies incur fewer costs in creating generic drugs (only the cost to manufacture, rather than the entire cost of development and testing) and are therefore able to maintain profitability at a lower price. The prices are low enough for users in many less-prosperous countries to afford them. For example, Thailand has imported millions of doses of a generic version of the blood-thinning drug Plavix (used to help prevent heart attacks), at a cost of 3 US cents per dose, from India, the leading manufacturer of generic drugs.[6]
In the UK, generic drug pricing is controlled only by the reimbursement price. Beneath this, the price paid by chemists and doctors is determined mainly by the number of licence holders, the sales value of the originator brand and the ease of manufacture. A typical price decay graph will show a 'scalloped' curve,[7] which usually starts out on the day of generic launch at the brand price, and then falls as competition intensifies. After some years, the graph typically flattens out at approximately 20% of the originator brand price. In about 20% of cases, the price 'bounces', which means some licence holders withdraw from the market when the selling price dips below their cost of goods. The price then rises for a while until they re-enter the market with new stock.[8][9]
Generic manufacturers do not incur the cost of drug discovery. Sometimes, reverse-engineering is used to develop bioequivalent versions to existing drugs.[10] Generic manufacturers also do not bear the burden of proving the safety and efficacy of the drugs through clinical trials, since these trials have already been conducted by the brand name company. (See the Approval and regulation section, below, for more information about the approval process.) The average cost to brand-name drug companies of discovering and testing a new innovative drug (with a new chemical entity) has been estimated to be as much as $800 million.[11] Merril Goozner estimates the true cost is closer to $100–$200 million.[12]
Generic drug companies may also receive the benefit of the previous marketing efforts of the brand-name drug company, including media advertising, presentations by drug representatives, and distribution of free samples. Many drugs introduced by generic manufacturers have already been on the market for a decade or more, and may already be well known to patients and providers (although often under their branded name).
For as long as a drug patent lasts, a brand name company enjoys a period of “marketing exclusivity” or monopoly, in which the company is able to set the price of the drug at a level which maximizes profitability. The profit often greatly exceeds the development and production costs of the drug. (This is partially offset by research and development of other drugs which do not make a profit.) The advantage of generic drugs to consumers comes in the introduction of competition, which prevents any single company from dictating the overall market price of the drug. Competition is also seen between generic and name-brand drugs with similar therapeutic uses when physicians or health plans adopt policies of preferentially prescribing generic drugs as in step therapy. With multiple firms producing the generic version of a drug, the profit-maximizing price generally falls to the ongoing cost of producing the drug, which is usually much lower than the monopoly price.[13]

Regulation

Most nations require generic drug manufacturers to prove their formulation exhibits bioequivalence to the innovator product.[14][15][16][17][17][18][19]
Bioequivalence, however, does not mean generic drugs must be exactly the same (“pharmaceutical equivalent”) as their innovator product counterparts, as chemical differences may exist (different salt or ester – a “pharmaceutical alternative”).[citation needed]

Efficacy


A bioequivalency profile comparison of 150 mg extended-release bupropion as produced by Impax Laboratories for Teva and Biovail for GlaxoSmithKline.

Oxybutynin

A 2009 Weill Cornell Medical College study concluded that patients switched to generic oxybutynin experienced a degradation in therapeutic value: "When we looked at changes in [prostate-specific antigen] (PSA) levels among men on Avodart switched to the generic formulation, we saw a greater than 0.75 ng/mL increase at 3 months in 34% of men. That is an increase that would ordinarily trigger a biopsy, but I put them back on the brand-name drug. The PSA came down in all cases, and none of them needed a biopsy", Steven A. Kaplan said of the findings.[20]

In the United States

Patent issues

Eligibility

When a pharmaceutical company first markets a drug, it is usually under a patent that, until it expires, allows only the pharmaceutical company that developed the drug (or its licensees) to sell it. Generic drugs can be produced without patent infringement for drugs where: 1) the patent has expired, 2) the generic company certifies the brand company's patents are either invalid, unenforceable or will not be infringed, 3) for drugs which have never held patents, or 4) in countries where the drug does not have current patent protection. Patent lifetime differs from country to country; typically an expired patent cannot be renewed. In the U.S., patent extensions may be granted if changes are made; some pharmaceutical companies have sought extensions on things as minor as changes to the shape and color of the pill; generic makers are excluded while the adjudication of the extension is considered. A new version of the drug with significant changes to the compound could be patented, but this requires new clinical trials. In addition, a patent on a changed compound does not prevent sales of the generic versions of the original drug unless regulators take the original drug off the market, as happened in the case of terfenadine.
This allows the company to recoup the cost of developing that particular drug. After the patent on a drug expires, any pharmaceutical company can manufacture and sell it; only manufacturing cost will be incurred, which is a small fraction of the cost of original testing and development of the drug.
In the U.S., the Patient Protection and Affordable Care Act, which President Obama signed on March 23, 2010, authorized the Food and Drug Administration to approve generic versions of biologic drugs and grant biologics manufacturers 12 years of exclusive use before generics can be developed. This biosimilar products are usually protected by surrounding patents which may also delay the time for their production.
When several top selling drugs go off-patent within a short period of time an interesting phenomenon called patent cliff arises opening opportunities for generic drug manufacturers.

Approval process

Enacted in 1984, the U.S. Drug Price Competition and Patent Term Restoration Act, informally known as the Hatch-Waxman Act, standardized U.S. procedures for recognition of generic drugs. An applicant files an Abbreviated New Drug Application (ANDA) with the Food and Drug Administration (FDA), and seeks to demonstrate therapeutic equivalence to a specified, previously approved “reference listed drug”. When an ANDA is approved, the FDA adds the drug to its Approved Drug Products with Therapeutic Equivalence Evaluations list, also known as the Orange Book, and annotates the list to show equivalence between the reference listed drug and the approved generic. The FDA also recognizes drugs using the same ingredients with different bioavailability, and divides them into therapeutic equivalence groups. For example, as of 2006, diltiazem hydrochloride had four equivalence groups, all using the same active ingredient, but considered equivalent only within a group.[21]
On October 4, 2007, FDA launched the Generic Initiative for Value and Efficiency, or GIVE.[22] GIVE will use existing resources to help FDA modernize and streamline the generic drug approval process. It also aims to increase the number and variety of generic drug products available. Having more generic-drug options means more cost-savings to consumers, as generic drugs cost about 30 percent to 80 percent less than brand name drugs.
In the United States, generic drug substances are named through review and recommendation of the United States Adopted Names (USAN) Council.

Exclusivity

The U.S. FDA offers a 180-day exclusivity period to generic drug manufacturers in specific cases.[23] During this period, only one (or sometimes a few) generic manufacturers can produce the generic version of a drug. This exclusivity period is only used when a generic manufacturer argues that a patent is invalid or is not violated in the generic production of a drug, and the period acts as a reward for the generic manufacturer who is willing to risk liability in court and the cost of patent court litigation. There is often contention around these 180-day exclusivity periods because a generic producer does not have to produce the drug during this period and can file an application first to prevent other generic producers from selling the drug.
Recently, the purpose of the exclusivity "bonus" provided for by the Hatch-Waxman amendments was turned on its head when the original patent holder, Cephalon, instituted patent infringement suits against all companies holding generic exclusivity rights to manufacture modafinil, the generic name for Cephalon's still-profitable stimulant drug, Provigil. "Settlement" of this suit with Cephalon was hardly a risky endeavor for the generic manufacturers, as it was Cephalon which agreed to pay Provigil's alleged infringers in excess of a billion dollars – if they agreed not to market generics for Provigil during their period of exclusivity. In effect, Cephalon was able to extend its exclusive right to manufacture Provigil even though Cephalon's patent for it had already run out.[citation needed]
Large pharmaceutical companies often spend millions of dollars protecting their patents from generic competition.[citation needed] Apart from litigation, companies use other methods, such as reformulation or licensing a subsidiary (or another company), to sell generics under the original patent. Generics sold under license from the patent holder are known as authorized generics;[24] they are not affected by the 180-day exclusivity period, as they fall under the patent holder's original drug application.
A prime example of how this works[25] is simvastatin (Zocor), a popular drug created and manufactured by US-based Merck & Co., which lost its US patent protection on June 23, 2006. India-based Ranbaxy Laboratories (at the 80 mg strength) and Israel-based Teva Pharmaceutical Industries (at all other strengths) received 180-day exclusivity periods for simvastatin; due to Zocor's popularity, both companies began marketing their products immediately after the patent expired. However, Dr. Reddy's Laboratories also markets an authorized generic version of simvastatin under license from Zocor's manufacturer, Merck & Co.; some packages of Dr. Reddy's simvastatin even show Merck as the actual manufacturer and have Merck's logo on the bottom.

Prolongation

Brand-name drug companies have used a number of strategies to extend the period of market exclusivity on their drugs, and prevent generic competition. This may involve aggressive litigation to preserve or extend patent protection on their medicines, a process referred to by critics as “evergreening”. Patents are typically issued on novel pharmacological compounds quite early in the drug development process, at which time the ‘clock’ to patent expiration begins ticking. Later in the process, drug companies may seek new patents on the production of specific forms of these compounds, such as single enantiomers of drugs which can exist in both “left-handed” and “right-handed” forms,[26] different inactive components in a drug salt,[27] or a specific hydrate form of the drug salt.[28] If granted, these patents ‘reset the clock’ on patent expiration. These sorts of patents may later be targeted for invalidation (“paragraph IV certification”)[29] by generic drug manufacturers.[30][31][32]

Quality standards

In the U.S., the FDA must approve generic drugs just as innovator drugs must be approved.[33] The FDA requires the bioequivalence of the generic product to be between 80% and 125% of that of the innovator product.[34]
This value range is part of a statistical calculation, and does not mean the FDA allows generic drugs to differ from the brand name counterpart by up to 25 percent. FDA recently evaluated 2,070 human studies conducted between 1996 and 2007, which compared the absorption of brand name and generic drugs into a person’s body; they were submitted to the FDA to support approval of generics. The average difference in absorption into the body between the generic and the brand name was 3.5 percent, comparable to differences between two different batches of a brand name drug.[35][36]
A physician survey in the US found only 17% of prescribing physicians correctly identified the USFDA's standards for bioequivalency of generic drugs.[37] A latest development to address this issue enables interested doctors and consumers to check generic drug interactions and outcomes detail to the specific drug and drug company.[38]
The generic equivalent of warfarin has only been available under the brand name Coumadin in North America until recently. Warfarin (either under the trade name or the generic equivalent) has a narrow therapeutic window and requires frequent blood tests to make sure patients do not have a subtherapeutic or a toxic level. A study performed in the Canadian province of Ontario showed that replacing Coumadin with generic warfarin was safe.[39] In spite of the study, many physicians are not comfortable with their patients taking the branded generic equivalents.[40] In some countries (for example, Australia) where a drug is prescribed under more than one brand name, doctors may choose not to allow the pharmacist to substitute a brand different from prescribed unless the consumer requests a generic brand.[41]
Generic versions of biologic drugs, or biosimilars, require additional tests to bioequivalency involving clinical trials for immunogenicity. These products cannot be entirely identical due to the batch to batch variability and their intrinsic biological nature and are governed by extra sets of rules by the FDA in the US and the EMA in Europe.[42]

Recalls

In 2007, North Carolina Public Radio's The People's Pharmacy "began collecting and reporting consumer complaints about generic Wellbutrin" yielding unexpected effects.[43] Subsequently, Impax Laboratories's 300 mg extended-release bupropion hydrochloride tablets, marketed by Teva Pharmaceutical Industries, were formally withdrawn from the U.S. market after being determined not bioequivalent by the FDA in 2012.[44][45]

Litigation

Two women, each claiming to have suffered severe medical complications from a generic drug, lost their Supreme Court appeal on June 23, 2011. In a 5-4 ruling, the justices found that generic drug companies do not share the same level of responsibility as makers of brand-name equivalents and do not have to update their warning labels when significant new risks emerge.[46]

List of pharmaceutical companies

The following is a list of the twelve largest health care companies ranked here by revenue as of March 2010 according to their released 2009 annual reports

Rank Company Country Total Revenues (USD billions) Total Revenues (reported currency in millions) Change 09/08 (%) Net income/ (loss) (reported currency in millions) Change 09/08 (%) R&D Expenses (reported currency in millions) Change 09/08 (%) Fortune 500 Ranking[1]
1 Johnson & Johnson[2] United States 61.90[3] $61,897 -2.9 $12,266 -5.3 6,986 -7.8 103
2 Pfizer[4] United States 50.01[3] $50,009 3.5 8,635 6.6 7,845 -1.3 152
3 Roche[5] Switzerland 47.35[3] 49,051 CHF 7.5 8,510 CHF -21.5 9,874 CHF 11.6 171
4 GlaxoSmithKline[6] United Kingdom 45.83[3] £28,368 16.5 £5,669 20.3 £4,106 11.5 168
5 Novartis[7] Switzerland 44.27[3] $44,267 6.8 $8,454 3.6 $7,469 3.5 183
6 Sanofi[8] France 41.99[3] €29,306 6.3 €8,471 17.9 €4,583 0.2 181
7 AstraZeneca[9] UK/Sweden 32.81[10] $32,804 3.8 $7,544 23.1 $4,409 -14.9 268
8 Abbott Laboratories[11] United States 30.76[10] $30,765 4.2 5,746 21.4 2,744 2.1 294
9 Merck & Co.[12] United States 27.43[10] $27,428 15.0 $13,024 64.2 $5,800 20.8 378
10 Bayer HealthCare[13] Germany 22.30 €15,988 3.8 €1,696 38.8 €1,845 5.9 154
11 Eli Lilly[14] United States 21.84[15] $21,836 7.2 $4,328 N/A N/A N/A 455
12 Bristol-Myers Squibb[16] United States 18.81[17] $18,808 6.2 $4,420 19.9 3,647 3.8 435
Some data have not been audited yet. Bayer has additional revenue not included here. The missing parts of the table will be added as more data are released by the companies.
The following is a list of the twelve largest healthcare companies ranked by revenue as of July 2009 in the Fortune Global 500.[1]
Rank[1] Company Country Total Revenues (USD millions) Net income/ (loss) (USD millions) Employees
1 Johnson & Johnson United States 63,747.0[18] 12,949.0 118,700
2 Pfizer United States 48,296.0[19] 8,104.0 81,800
3 GlaxoSmithKline United Kingdom 44,654.0[20] 8,438.6 99,003
4 Roche Switzerland 44,267.5[21] 8,288.1 80,080
5 Sanofi-Aventis France 42,179.0[22] 5,636.7 98,213
6 Novartis Switzerland 41,459.0[23] 8,195.0 96,717
7 AstraZeneca United Kingdom/Sweden 31,601.0[24] 6,101.0 65,000
8 Abbott Laboratories United States 29,527.6[25] 4,880.7 68,838
9 Merck United States 23,850.3[26] 7,808.4 55,200
10 Wyeth United States 22,833.9[27] 4,417.8 47,426
11 Bristol-Myers Squibb United States 21,366.0[28] 5,247.0 35,000
12 Eli Lilly United States 20,378.0[29] (2,071.9) 40,500
The following is a list of the 49 largest companies involved in pharmaceutical and biotech industry ranked by healthcare revenue as of 2008.[30] Some companies (e.g., Bayer) has additional revenue not included here.[31][32]
Rank[30] Company Country Total Revenues (USD millions) Healthcare R&D 2008 (USD millions) Net income/ (loss) 2008 (USD millions) Employees 2008
1 Pfizer[33] (with Wyeth[34]) United States 70,696 11,318 14,111 137,127
2 Johnson & Johnson United States 63,747 NA 10,576 119,200
3 Hoffmann–La Roche Switzerland 43,970 NA 8,135 78,604
4 Novartis Switzerland 41,460 NA 11,946 98,200
5 GlaxoSmithKline United Kingdom 40,424 6,373 10,432 103,483
6 Sanofi-Aventis France 40,328 NA 7,204 99,495
7 AstraZeneca United Kingdom/Sweden 31,601 NA 5,959 67,400
8 Abbott Laboratories[35] United States 29,527 2,688 4,880 68,697
9 Merck & Co. United States 23,850 4,678 7,808 74,372
10 Bristol-Myers Squibb United States 19,977 NA 2,165 42,000
11 Eli Lilly and Company United States 18,634 NA 2,953 40,600
12 Boehringer Ingelheim Germany 16,959 1,977 2,163 43,000
13 Takeda Pharmaceutical Co. Japan 15,697 1,620 2,870 15,000
14 Bayer [36] Germany 15,407 3,770 6,448 108,600
15 Amgen United States 14,771 3,366 3,166 48,000
16 Genentech United States 13,400 15773 3,640 33,500
17 Baxter International United States 12,300 614 1,397 38,428
18 Teva Pharmaceutical Industries Israel 11,080 495 546 26,670
19 Astellas Pharma Japan 10,701 1,435 1,122 23,613
20 Daiichi Sankyo Japan 9,682 1,459 671 20,100
21 Novo Nordisk Denmark 9,081 1,063 1,922 26,575
22 Procter & Gamble United States 8,964 NA 10,340 29,258
23 Eisai Japan 5,583 926 604 14,993
24 Merck KGaA Germany 5,175 772 1,258 13,900
25 Alcon United States 4,897 512 1,348 13,500
26 SINOPHARM China 4,700 498 1249 9700
27 Akzo Nobel Netherlands 4,694 741 1,449 13,000
28 UCB Belgium 4,426 1,024 492 12,741
29 Nycomed Switzerland 4,264 NA -105 10,533
30 Forest Laboratories United States 3,442 941 454 9,649
31 Solvay Belgium 3,268 533 1,026 9,000
32 Genzyme United States 3,187 650 -17 8,477
33 Allergan United States 3,063 1,056 -127 8,423
34 Gilead Sciences United States 3,026 384 -1,190 6,772
35 CSL Australia 2,788 161 454 6,400
36 Chugai Pharmaceutical Co. Japan 2,787 467 328 5,962
37 Biogen Idec United States 2,683 718 218 5,907
38 Bausch & Lomb United States 2,292 197 15 5,830
39 Taiho Pharmaceutical Co. Japan 2,069 244 132 5,756
40 King Pharmaceuticals United States 1,989 254 289 5,191
41 Watson Pharmaceuticals United States 1,979 131 -445 5,126
42 Mitsubishi Pharma Japan 1,945 403 208 5,111
43 Shire United Kingdom 1,797 387 278 4,958
44 Cephalon United States 1,764 403 145 4,913
45 Dainippon Sumitomo Pharma Japan 1,763 350 193 3,750
46 Kyowa Hakko Japan 1,698 268 108 2,895
47 Shionogi Japan 1,640 320 159 2,868
48 Mylan Laboratories United States 1,612 104 217 2,800
49 H. Lundbeck Denmark 1,552 329 186 2,515


Alphabetical listing

It is limited to those companies notable enough to have articles in Wikipedia.

1-A

B-D

E-L

M

N

O

P

R

S-T

U-Z