**9. References**

ANSI/ASHRAE STANDARD 94.1-2002. (2006). *Method of Testing Active Latent-Heat Storage*

Arkar, C. & Medved, S. (2005). Influence of accuracy of thermal property data of a phase

Arkar, C.; Vidrih, B. & Medved, S. (2007). Efficiency of free cooling using latent heat storage

Bakenhus, B.H. (2000). Ice storage project. *ASHRAE J*, (May 2000), Vol. 42, No. 5, pp. 64-66,

Bony, J. & Citherlet, S. (2007). Numerical model and experimental validation of heat storage

Butala, V. & Stritih, U. (2009). Experimental investigation of PCM cold storage. *Energy Build*,

Del Coz Díaz, J.J.; García Nieto, P.J.; Lozano Martínez-Luengas, A. & Suárez Sierra, J.L.

Dolado, P.; Lazaro, A.; Zalba, B. & Marín, J.M. (2007). Numerical simulation of heat transfer

Dolado, P.; Lazaro, A.; Marin, J.M. & Zalba, B. (2011a). Characterization of melting and

Dolado, P.; Lazaro, A.; Marin, J.M. & Zalba, B. (2011b). Characterization of melting and

*Devices Based on Thermal Performance* (ANSI approved), recently replaced by

change material on the result of a numerical model of a packed bed latent heat storage with spheres. *Thermochim Acta*, (Aug 2005), Vol. 438, No. 1–2, pp. 192–201,

integrated into the ventilation system of a low energy building. *Int J Refrig*, (Jan

with phase change materials. *Energy Build*, (Oct 2006), Vol. 39, No. 10, pp. 1065–

(2010). A study of the collapse of a WWII communications antenna using numerical simulations based on design of experiments by FEM. *Eng Struct*, (Jul 2010), Vol. 32,

in phase change materials (PCM) for building applications. *Proceedings of Heat transfer in components and systems for sustainable energy technologies*, 2-9502555-3-1,

solidification in a real-scale PCM-air heat exchanger: Numerical model and experimental validation. *Energy Conv Manag*, (Nov 2010), Vol. 52, pp. 1890-1907,

solidification in a real-scale PCM-air heat exchanger: Experimental results and empirical model. *Renew Energy*, (Apr 2011), Vol. 36, pp. 2906-2917, 0960-1481.

Bi · enc *air enc h e*

**9. References**

DOE Design of Experiments

PCM Phase Change Material

TES Thermal Energy Storage 1D One Dimensional

ASHRAE 94.1-2010.

0040-6031.

0001-2491.

0196-8904.

1072, 0378-7788.

No. 7,pp. 1792-1800, 0141-0296.

Chambery, France, April 2007.

HTF Heat Transfer Fluid

DSC Differential Scanning Calorimetry

PID Proportional Integral Derivative

2007), Vol. 30, No. 1, pp. 134-143, 0140-7007.

(Mar 2009), Vol. 41, No. 3, pp. 354-359, 0378-7788.

HVAC Heating, Ventilation, and Air Conditioning

**17**

*Sweden*

Mohamad Kharseh

*Willy´s CleanTech AB, PARK 124 Karlstad,*

**Ground-Source Heat Pumps and Energy Saving**

The global warming itself and its consequences cause considerable problems. It results in extreme climate events such as droughts, floods, or hurricanes, which are expected to become more frequent. This puts extra strain on people and has great impact on public

Internationally, there is a political understanding that global warming (or climate change) is the main challenge of the world for decades to come. Thus, all states must work together in

Although, studies suggest that there is indeed relationship between solar variability and global warming (Lean and Rind, 2001), two causes of the warming have been

This implies that current warming is anthropogenic and caused by human activities, i.e. global use of non-renewable energy. So far, the total global energy consumption has already

Much of the energy used worldwide is mainly supplied by fossil fuels (~85 % of the global energy demand while renewable energy sources supply only about 6 %) (Moomaw et al., 2011, Jabder et al., 2011, Jaber et al., 2011). Owing to global dependence on oil fuels has resulted in a daily oil consumption of 87.7 million barrels (Mbbl), Fig. 1 (IEA, 2010, EIA, 2007). Consequently, about 3.1010 ton of carbon dioxide emissions are annually emitted into the atmosphere. In other word, for each consumed kWh about 205 kg of carbon dioxide is

Environmental reasons urge us to find more efficient ways in converting and utilizing the energy resources. From the environment point of view, there is now almost universal scientific acceptance that profligate energy use is causing rapid and dangerous changes in the global climate. There is mounting evidence that the mean global temperature has increased over the period 1880 to 1985 by 0.5 to 0.7 oC (Hansen and Lebedeff, 1987). While surface air temperature (SAT) compilations shows that SAT has increased 1.2 oC last century. If a current climatic change trend continues, climate models predict that the

1010 MWh/year and it is projected to have an annual growth rate about 1.4 %

1. related to the accumulation of greenhouse gases in the Earth's atmosphere;

2. related to heat emissions (Nordell, 2003, Nordell and Gervet, 2009).

**1. Introduction**

suggested:

exceeded 15.

until 2020 (EIA, 2010).

being emitted into the atmosphere.

health and life quality especially in poor countries.

order to overcome climatic change consequences.


**3. A single extraction study of a metal-polluted mine waste of Central Mexico**

### **3.1 Introduction**

In this study, we focused mainly on lowering the bioavailability and mobility of Cd, Cu, Pb, and Zn below official environmentally safe values and to warrant a biologically clean and sustainable ecosystem. To reach this goal, two schemes were visualized. First, we assayed the addition of widely used agronomic materials consisting of lime (Ca(OH)2); gypsum (CaSO42H2O); P-fertilizer (KH2PO4) and compost to "treat" a gradient of soil-fresh mine tailings mixtures to assess the treatment efficacy to abate the levels of the most toxic metal species available for plant growth; in solution, the free metal ion activity, (M2+)-value, for Cd2+, Cu2+, Pb2+, and Zn2+; and on the solid phase; the so-called DTPA-phytoavailable [17], and the acidsoluble fraction imposed by some international [22, 120] standards, and a national norm [23–28]; second, a bioassay was applied to find the conditions that allowed a sensitive indicator plant to grow in these "fertile" ameliorated media. Our studies proved to be useful in deriving soil-substrate quality criteria to establish specific strategies to verify the success of remediation processes. To evaluate the HM-toxicity abatement, both the bioavailable (acid-extractable) HM fraction and the chemical activity of the free metal ion, (M2+) were measured after incubation with the agrostabilizing treatments. Acid drainage was emulated using the standardized acetic acid extraction procedure required by norms [23–28] and standards [22, 121].

### **3.2 Water, DTPA, and acid-extractable heavy metal levels**

Extraction solutions to evaluate water-DTPA- and acid-extractable solutions consisted of 1) H2O-CO2 [24, 120] as saturation extract; 2) 1:2 ratio DTPA-extraction [17, 22], and 3) acetic acid (HAcO)-extraction [22], were used to obtain different species and fractions of metals from soil, mine waste, and mixtures. Extracts were analyzed for total dissolved Cd, Pb, Cu, and Zn by FAAS. Initial and in equilibrium (after incubation) extractable levels of metals, [M]HAcO, were determined at a 1:20 solid:liquid ratio in 0.2 M CH3COOH. Equilibrium-free HM ion activities, (M2+), were determined in the aqueous extracts of the treated mixtures by ASV [55, 56]. Calculations of (M2+) were carried out with MINEQL+ software [66, 67].

### **3.3 Experimental substrate mixtures and agrochemical treatments**

Enough total mass for speciation studies and bioassays of six different substrate systems were prepared by mixing soil and mine tailings at various ratios (w/w) to emulate different degrees of soil pollution as follows: A (100:0%), B (80:20%), C (60:40%), D (40:60%), E (20:80%), and F (0:100%) soil:mine waste material. The four agrochemical treatments tested consisted in adding lime [Ca(OH)2], gypsum [CaSO4�2H2O], P-fertilizer [KH2PO4], and compost [OM] at three different doses. Agronomic materials were stoichiometrically formulated according to the initial sum of the Cd, Cu, Pb, and Zn extractabilities in 0.2 N HAcO (highest dose), DTPA (medium dose), and H2O-CO2 (lowest dose). Compost dose was added to reach 5, 10, and 20% (w/w) of OM. Blank and treated mixture systems were incubated for three weeks to reach equilibrium, adding water to keep a 1:2.5 solid:liquid ratio. For Pfertilizer, the stoichiometric addition also considered the amount of exchangeable Ca2+ levels. This test helped to discriminate treatments that efficiently decreased the HM-extractable contents from those shown by the untreated blank mixtures.

### **3.4 Toxicity bioassays**

This bioassay was carried out only for the PO4 and OM treatments following international standard instructions (ISO 1993 [29], ISO 2005 [30]). At least seven barley (*Hordeum vulgare*) plants per experimental unit were grown in 100 mL black conical plastic pots (max/min radii of 3.7/1.9 cm and 5 cm height) to contain ca. 140 g of material of each of the six soil-mine waste mixtures, including the four ameliorating treatments and the three doses to give a total 72 pot systems. Root length was measured [32] and statistically analyzed with a 95–99% Fisher test of significance against the HM extracted from the mixture systems as an indicator to evaluate the efficacy of treatments and doses to lower the HM toxic effects and to assess the cleanness of the treated polluted mixtures.

### **3.5 Results**

The presence of high amounts of Pb and Zn is common in Zimapan and they are found in combination with As, mainly in minerals of arsenopyrite (AsFeS), scorodite (FeAsO4�2H2O), and in association with pyrrhotite (Fe1-xS), pyrite and marcasite (FeS2), sphalerite (ZnS) and galena (PbS), very common minerals in the area of Zimapan [3] such that As-levels are within the reported values for this element in soils which were 19–17,384 ppm in Mexico [121–124] and within 5200–40,853 ppm in mine tailings of Zimapan [3, 122, 125]. Regarding the four metals of interest levels found were within the reported values for soils 15–7200 ppm for Cu, 31–3400 ppm for Pb, and 26–6270 ppm for Zn [68, 122, 123], whereas for mine wastes in the country, our results were within the reported ranges of 186–2787 ppm, 910–9500 ppm, and 2218– 32,400 for the same metals, respectively [3, 121, 122]. Official Mexican regulations [23] established levels of Cd and Pb in soils of the order of 100–300 and 3–5 mg kg�1 , respectively, as hazardous to crops. These limits were not exceeded in the soil sample extracts obtained with 0.2 M HAcO. Regarding Cu and Zn, levels higher than 0.2 mg kg�1 and 1.0 mg kg�1 , respectively, are reported as adequate for these micronutrients [23]. Accordingly, levels of Cd and Pb in mine tailing must not exceed 24 mg kg�1 and 120 mg kg�1 , respectively, in the aqueous and/or HAcO extracts, so that Pb is not within the allowable levels when extracted with HAcO 0.2 M [26].

Zn and Cu are not potentially toxic elements regulated by Mexican official norms. The efficacy of the agronomic treatments was evaluated by comparing the initial and final quantities of the studied metals, based on the acid-extractable fraction for each experimental mixture. **Figure 2** shows, in contrast with reported values, which found more than 87% decrease of the HCl-extractable concentrations of Cd, Cu, Pb, and Zn in polluted soils, after a combined CaCO3-CaHPO4 stabilizer was added [126], in our studies when agricultural lime and gypsum were applied, the [M]AcO-extracted did not show a significant HM level decrease, with respect to their initial concentrations, as compared with controls (see gypsum and lime graphs in **Figure 2**), moreover, redissolution process was observed for all metals except for Pb in the case of gypsum, and with some tendency to positive results for the E and F systems for Cu, Pb, and Zn. For Cd, gypsum worked well only when the soil fraction dominated (systems A, B, and C at lowest dose) but, in general, without significant differences between blank and treatments (F-test, 95%). In contrast with lime and gypsum, P-fertilizer showed excellent results (see **Figure 2** at lower left) when suppressing the acid-extractable levels of Cd, Pb and Zn at any dose getting for the latter diminutions of 92% of initial quantities. For Pb the lowest dose showed a biphasic behavior indicating there exist two distinct sites for sorption which agrees with results found elsewhere [127]. For Cu, a significant decrease of [M]AcO was observed only when the dose and mine

### **Figure 2.**

*Effect of adding ameliorating materials lime, Ca(OH)2 (upper left), gypsum, CaSO4*�*2H2O (upper right), Pfertilizer, KH2PO4 (lower left) and OM-compost (lower right), at low, medium, and high doses, over the 0.2 M acid-extractable levels (mg kg*�*1 ) of Cd, Cu, Zn, and Pb (Y-axis), for six experimental mixtures soil:mine waste (s:mw): A: 100% soil, B: 80:20 s:mw, C: 60:40 s:mw, D: 40:60 s:mw, E: 20:80 s:mw, F: 100% mw. Curves show in yellow-orange the blank treatment (no ameliorating material); blue the low dose (ameliorating materials added based on the sum of the four concentrations of water-soluble metals); purple the medium dose (based on the sum of the four concentrations of the DTPA-extractable metals); and red the high dose (based on the sum of the four concentrations of the acid-extractable metals). For OM-compost, low, medium, and high doses were added to reach 5% (low dose), 10% (medium), and 20% (high dose) OM levels (w/w-basis), for the water-soluble, DTPAextractable, and acid-extractable metals, respectively.*

tailing contents were highest for systems C to F (F-test, 95%). **Figure 2** also reveals that compost showed the best results of all amending materials where HM level suppression was more homogeneous. For Cd and Zn this treatment showed a significance reduction of the extractable metal levels at the three doses tested, although results for Zn were much more pronounced. For Cu and Pb the decrease of the extractable metal where mine tailing material was higher (systems D to F) the abatement was significant with respect to the blank system A. However, where the soil was pure or slightly polluted (systems A to C) the effect was not significant, especially for Cu-lowest and medium doses where even the metal extractability increased. For Pb, only the highest and medium doses showed some efficacy in suppressing these values. Note again the biphasic sorption for Cu and Pb at all doses, but more pronounced at the lowest one. These results completely correspond with those obtained by other authors [128–130]; who added composts, biosolids, manure, and peat materials effectively reducing Cd, Pb, and Zn mobility. These results were also consistent with the aqueous free metal, [M2+] ac, levels determined by ASV (not shown). Increment in the doses produced an important drop in the activity of this toxic chemical species even in the pure tailing systems, obtaining, in the best case, a diminution of three to five orders of magnitude orders, for example, Cu and Cd system-E treated with OM, respect to control.

### **3.6 Biotoxicity assays**

Toxicity bioassay systems (A to F) and the P-fertilizer and compost treatments were tested at the medium doses, with the only intention of evaluating if there was a chance for a positive response when applying these amending materials and the indicator-sensitive plant could prove a fertile non-toxic media was created. Root length was the agronomic parameter measured [29, 30]. Fisher test was applied to root length (95% significance) to see differences among soil-mine waste mixture treatments (OM and P-fertilizer) and doses (low, medium, and high). **Figure 3** shows the results of these analyses. The effect of treatments including the null one was

### **Figure 3.**

*Histograms show the root length (cm) of barley (*Hordeum vulgare) *plants as affected by treatments. Upper row shows the results for the blank and compost added; lower row shows the results for blank and P-fertilizer, KH2PO4 added, both at low, medium, and high doses, respectively. Different lower-case letters mean significant differences among treatments, according to Fisher's test of 95% significance. Low, medium, and high PO4-doses were added based on the sum of the four concentrations of the water-soluble, DTPA-, and acid-extractable metals, respectively). For OM-compost, low, medium, and high doses corresponded to 5%, 10% and 20% (w/w-basis), respectively.*

investigated in the six soil:mine waste systems to evaluate the effect of mine waste incorporation and predominance in these emulated scenarios of polluted soils.

**Figure 3** shows that roots growing in the different mixture systems were considerably affected because of the increasing content of mine waste material added to the pristine soil, having a shortage of more than 75% of the length, when exposed to pure mine waste (blank-mixture F), respect to the pure soil (blank-mixture A). With the presence of P-fertilizer or OM treatments, a significant increment in root length with respect to control systems (PO4- and OM-mixture F) was observed, especially for the pure mine tailing mixtures (PO4-mixture F), where the highest doses improved the growth remarkably. The addition of P-fertilizer in medium and high doses was effective in providing a good media for the growth of the sensitive plant in pure mine tailing whereas compost as shown by the good response of root growth when the dose was highest. Based on these findings, it results clear the DTPA- and the acidextractable levels of Cd, Cu, Pb and Zn, gave a good indication of the phytoavailability-phytotoxicity levels being suppressed by the ameliorating material added. PO4-medium and high doses effectively corrected most of the growing problems shown on the blank (not amended) treatment and on the low doses of PO4 added which was based on the sum of all four water-extracted metals. For the OM-compost treatments, it is important to note that low, medium, and high OM levels were chosen based on what is recommended for optimum growth of plants, according to what FAO and other OM classifications suggest which consider 5–6% as the minimum good OMlevel to improve soil fertility [23].


**4. Participation of the elderly**

From the outset of the programme, the ZonMw committee worked to ensure that elderly people were not only the object of inquiry and research in the programme but were also included as subjects and participants. The elderly people were encouraged to participate in the geriatric networks and in working groups. As a result, the focus of empirical research on medical care innovation shifted over time, based partly on what elderly people themselves considered being important. This in turn led to an increasing emphasis on welfare and support of the elderly in the continuum of well-being and care.

Initially, elderly people had to become accustomed to participating in a professional setting. Collaboration between volunteers (the elderly people) and professionals cannot be taken for granted and requires commitment from everyone involved. Elderly people were trained to discuss project proposals, procedures and outcomes with professionals. Frail elderly people were not involved in these procedures. However, as the active elderly people had regular contact with the frail elderly people, the voices of the frail elderly people could be included in the working groups. Embedding elderly people in the organisation of the networks and involving them in projects and research meant that all networks had a strong core group of active elderly people. The project outputs were better suited to elderly people's needs because elderly participants were included in target group panels and advisory boards. For example, participants proposed improved integration of medical care and welfare and more preventive activities.

A new phenomenon is the involvement of elderly people in education, not just occasionally but as a structural part of the curriculum. This occurs especially where colleges and universities train students to work as professionals—nurses, doctors, physiotherapists, and psychologists, for example—with elderly people. Elderly people participate as teachers in various roles, for example, as patient, guest lecturer, mentor or co-supervisor of theses. They also participate in research, in focus groups and in training groups. The combination of elderly and young people has proved to be valuable to everyone concerned. Elderly people have also been asked to participate in technical and vocational training programmes. The Organization of Elderly (*DenkTank 60+ Noord* in Dutch) has five research and development education groups. The demand for elderly is now greater than the offer.


7. Conclusions

capacitance of f-SWCNT/Co3O4 is high with a value of 343F=g, while that of the Co3O4 nanoparticles is only 77F=g (Figure 17). Zarnegar et al. [27] used a new sonochemical synthesis of polyhydroquinolines having as catalyst Co3O4-CNT nanocomposites for aldehydes, dimedone, ethyl acetoacetate, and ammonium acetate in an ethanol medium. These nanocomposites proved to be a highly effective

TEM results of MWCNT-Co3O4 nanoparticles [27], (a) Co3O4, (b) MWCNT, (c) MWCNT-Co3O4

nanoparticles at 100 nm range and (d) MWCNT-Co3O4 nanoparticles at 100 nm range.

Figure 17.

Figure 18.

46

Synthesis procedure of MWCNT-Co3O4 nanoparticles [26].

Cobalt Compounds and Applications

The cobalt oxide-based composite nanoparticles and its engineering and medical applications were discussed in this book chapter. The pure Co3O4 nanoparticles reveal the presence of toxicity, whereas cobalt compounds are nontoxic. In this book chapter, the synthesis procedure for cobalt and cobalt-based compounds such as GO/Co3O4, ND-Co3O4, zeolite Y/Co3O4, and MWCNT-Co3O4. All the synthesized cobalt-based compound materials present magnetic properties, which can be benefit for the thermal applications, electrical applications, and medical applications. Cobalt oxide-based compounds have improved synergistic properties as compared to pure cobalt oxide nanoparticles.

### Acknowledgements

The author (LSS) acknowledges the Foundation for Science and Technology (FCT, Portugal) for the financial support received through the grant SFRH/BPD/ 100003/2014. The author (ACMS) acknowledges the 2017 Visiting Scientist Fellowship awarded to him under the Chinese Academy of Sciences President's International Fellowship Initiative. TEMA/DEM researchers also acknowledge the FCT grant UID/EMS/00481/2019-FCT, the infrastructures support CENTRO-01-0145- FEDER-022083-Centro Portugal Regional Operational Programme (Centro2020), and Project 33912-AAC no. 03/SI/2017, under the Portugal 2020 Partnership Agreement, through the European Regional Development Fund.

## Author details

Lingala Syam Sundar1 \*, Manoj K. Singh1,2\*, António M.B. Pereira1 and Antonio C.M. Sousa1

1 Department of Mechanical Engineering, Centre for Mechanical Technology and Automation (TEMA-UA), University of Aveiro, Portugal

2 Centre for Nano and Material Sciences, JAIN (Deemed-to-be University), Bengaluru, Karnataka, India

\*Address all correspondence to<EMAIL_ADDRESS>and<EMAIL_ADDRESS>
© 2019 The Author(s). Licensee IntechOpen. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/ by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


**5. Conclusions**

In the present study, a GWAS for mesocotyl length in 208 rice accessions was conducted. Mesocotyl length varied in di fferent culture conditions and sowing depths. GWAS have identified 16 loci significantly associated with mesocotyl elongation, which explained phenotypic variations ranged from 7.1% to 10.0%. Furthermore, five high-confidence candidate genes were identified on chromosomes 1, 3, 5, 9 and 12. The accessions with longer mesocotyl and the markers significantly associated with mesocotyl length can be used to promote the process of rice breeding. This study will facilitate our uanderstanding on the genetic architecture of rice mesocotyl length.

**Supplementary Materials:** The following are available online at http://www.mdpi.com/2073-4425/11/1/49/s1, Table S1: Detailed information of 208 rice accessions, Table S2: SNPs significantly associated with mesocotyl length under different environments, Table S3: Candidate genes for mesocotyl length in 208 rice landraces or varieties, Table S4: Accessions used in qRT-PCR analysis, Table S5: Primers used in this study. The raw Illumina sequencing data will be available upon the request.

**Author Contributions:** Conceived and designed the experiments: H.L., Y.W., G.Y. Performed the experiments: H.L., J.Z., X.L. Analyzed the data: H.L., J.L. (Jiaolong Li), G.Y. Wrote and revised the paper: H.L., J.Z., J.L. (Jindong Liu), Y.W., G.Y. All authors have read and agreed to the published version of the manuscript.

**Funding:** This work was supported by Agricultural Science and Technology Innovation Program Cooperation and Innovation Mission (Grant No. CAAS-XTCX2016001) and Shenzhen Science and Technology Projects (No. JSGG20160608160725473).

**Acknowledgments:** We thank Guosheng Xiong for providing some of the germplasms used in this study. We are grateful to the field research assistant Bingmei Lin in phenotyping and other field work.

**Conflicts of Interest:** The authors declare no conflict of interest.


*2.1. Phase-Appropriate Approach*

A phased approach to the development and implementation of bioassays for biotherapeutics is widely accepted by industry and regulatory agencies, and the similar principles apply to bispecific therapeutics. It is often advantageous and preferred to start with a binding method for the early phases of product development. Most commonly implemented binding assays include enzyme-linked immunosorbent assays (ELISAs) or surface-plasmon resonance (SPR) technologies. More complex and MoA-reflective cell-based bioassays are developed by later phases, and they are validated before marketing application submission. However, it is recommended that a relevant MoA-based bioassay is developed earlier, not only to gain a greater process and product understanding but also to gain a better understanding of the method's performance prior to pivotal clinical trials. Cell-based bioassays should be qualified and monitored over the span of the clinical development to have a true understanding of the critical steps and components of the assay in most cases. The selection of the bioassay should be driven by the product's therapeutic MoA. In cases where the MoA is simply binding to a target, a surrogate method, such as a protein binding or competitive binding assay, may be sufficient to determine potency. Developing robust and quality-control (QC)-suitable cell-based bioassays is more challenging than developing non-cell based binding assays [71,72]. There are case studies of implementing surrogate, non-cell-based bioassays in the commercial control system if the surrogate assay

has demonstrated a good correlation in a bridging study using degraded product and other samples with the MoA-reflective cell-based assay.

#### *2.2. Mechanism of Action*

Design strategies for bioassays are driven by the drug's intended physiological MoA. Unlike other analytical techniques, bioassays are almost always unique for each therapeutic. A well-designed bioassay will accurately capture the biological activity of a drug candidate. As shown in Figure 2, common MoAs of bispecific therapeutics include direct binding to soluble targets (e.g., ligands, cytokines and enzymes), or to cell-surface receptors in either an inhibitory or agonistic manner.

Each MoA will require a different approach when considering the bioassay design. In the case of BsAbs and related recombinant proteins, secondary, tertiary, or synergistic MoAs may be discovered during development. This biological complexity further contributes to the challenge of developing MoA-reflective assays to capture the candidate molecule's putative therapeutic biological activity [50,73–76]. In some cases where multiple MoAs exist in a single molecule, a combination assay that measures all MoAs in a single assay may be suitable for product release and stability testing, with secondary characterization assays developed to measure the individual activities of each MoA if applicable. Otherwise, multiple bioassays would be necessary to fully characterize the molecule's activity. It is not required to have all bioassays for release, instead only the assay with the most MoArelevant and stability indicating bioassay can be selected as the release potency assay while the other assays are used for characterization.

#### *2.3. Overall BsAb Characterization Strategy*

Efficacy and safety assessments of BsAbs rely on the successful development of a pharmacologically and clinically relevant bioanalytical strategy that most importantly can reflect the biological activities of these dual-targeting antibodies and can differentiate higher order structure, potency, and efficacy.

It is most vital to develop characterization and bioanalytical approaches to study important quality attributes [77] including overall stability, fragmentation/aggregation/ immunogenicity, antigen specificity, affinity, on and off rates, avidity (for molecules with two targets on the same cell), and MoA/biological activity.

While BsAbs require bioassays to measure two binding events, the choice of the appropriate bioassay will also depend on the assay format, assay platform, critical reagents, and, importantly, the BsAb target profile. Following the successful development of the pharmacologically relevant BsAb format, the analytical strategy is outlined to first characterize the independent or simultaneous binding affinities and the preferential binding of BsAb to their dual-antigen targets. Widely used bi-functional quantitative assay formats to enable target-specific capture and detection of binding properties include flow cytometry and ligand-binding immunoassay setups. A range of other assay platforms (ELISA, SPR, ADCC, competitive flow cytometry, etc.), whose selection relies on BsAb format, MoA, and target profile, are used to address bioanalytical questions for BsAbs. These assays are listed in Table 1 and further discussed in Section 3.

Meaningful bioanalytical approaches are also needed for immunogenicity and PK/PD assessments to determine the safety and efficacy of BsAbs [78,79]. Immunogenicity is defined as the unwanted immune response of the host against the therapeutic BsAb. In addition to altering the PK of a target through changing its clearance, immunogenicity is responsible for infusion-related reactions and in some cases, reduced treatment efficacy [80]. Immunogenicity is clinically assessed by the detection of anti-drug antibodies, consisting of IgM, IgG, IgE, and/or IgA isotypes [81]. The bioassays employed to assess immunogenicity include binding immunoassays such as ELISA to detect all isotypes capable of binding the therapeutic BsAbs, and neutralization assays (in-vitro cell-based assays or competitive ligand-binding assays) directed at the biologically active site, to inhibit the functional activity of BsAb. Major histocompatibility complex-II (MHC-II)-Associated Peptide Proteomics

(MAPPs) assay can screen and quantitate naturally processed and presented MHC-II peptides on the surface of antigen-presenting cells, which are then further characterized for immunogenicity using in-vitro assays. T-cell epitope-mapping prediction tools are also used to identify the CD4 T cell epitope within the amino acid sequence of the therapeutic antibody and determine the strength of peptide binding to HLA molecules [82,83]. PK for biologics is often at least partially determined by FcRn-mediated recycling. In-vitro assays designed to measure binding of a therapeutic antibody to FcRn via its Fc domain, including SPR-based FcRn binding assays and FcRn-affinity chromatography, have been shown to be indicative of FcRn-mediated clearance and are frequently used to assess potential impacts to PK [84,85].

**Table 1.** List of bioassays for bispecific molecules.

BsAbs: bispecific antibodies; ELISA: enzyme-linked immunosorbent assay; HRP: horseradish peroxidase; IFN-g: interferon gamma; LDH: lactate dehydrogenase; MoA: mechanism of action; NFAT: nuclear factor of activated T cells; SPR: surface-plasmon resonance; VH: variable heavy domain; Ang-2: angiopoietin-2; VEGF: vascular endothelial growth factor; PD-L1: programmed death-ligand 1; CSPG: chondroitin sulfate proteoglycan.

### **3. Bioassays for Bispecific Antibodies and Case Studies**

*3.1. Bioassays for Biotherapeutics*

For biotherapeutics, a selective, physiologically relevant bioassay is essential to report on the product's potency and stability, by providing an assessment of the molecule's biological activity. Bioassays, in principle, can range from recognition of a particular antigen in a simple binding method, through systems as complex as blocking an inhibitory ligand that restores a co-stimulatory effect in a cell-based method. Selection of an appropriate method has its challenges rooted not only in the need to mimic the MoA, but also because bioassays can be costly to develop, perform, transfer, and maintain. Despite efforts to implement measures to ensure method control, cell-based bioassays can be inherently variable and often lack the precision and robustness of biophysical methods simply because they use living organisms, tissues, or cells.

While the general principles of bioassay design and strategy (e.g., measuring antigen target binding and biological activities) apply to bispecific antibodies, developing bioassays for bispecific antibodies requires unique considerations as bispecific antibodies bind two different targets with distinct mechanisms of action from monospecific biotherapeutics. A diverse range of bioanalytical assays have been developed and employed to study BsAbs, including methods designed to assess binding, potency, biological function, and purity. Figure 3 depicts a few of the methods involved in the various types of BsAb bioassays, which are further discussed in the following sections, and case studies are summarized in Table 2.

**Figure 3.** Representative bioassays for BsAb: (**a**) Reporter gene T-cell activation assay; (**b**) Single-arm binding SPR assay; (**c**) Cell proliferation assay; (**d**) Bridging ELISA. MTT:3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyl-2H-tetrazolium bromide.

**Table 2.** BsAb categories and potential bioassays applicable: Summary of case studies.

BLI: biolayer interferometry; TR-FRET: time-resolved fluorescence resonance energy transfer.

#### *3.2. BsAb Bioassay: Binding Assays*

ELISA and SPR are commonly used for in-vitro characterization of antigen binding for BsAbs. ELISAs are advantageous in that they are sensitive, typically fast to develop compared to cell-based assays, relatively inexpensive, and can be performed in complex matrices (e.g., cell lysates) [98,99]. Bridging ELISAs and competitive binding ELISAs can also provide information on the ability of the BsAbs to bind both antigens simultaneously, and they can therefore potentially be used as MoA-reflective potency assays, at least during initial development phases. The case studies presented below provide examples of competitive and bridging ELISAs used to confirm the simultaneous binding of two different targets for a tetravalent IgG-like BsAb. Despite their advantages, ELISA assays have drawbacks, one of which is that they are end-point assays and do not provide information on binding kinetics such as on and off rates [100]. In contrast, SPR measures continuous binding in a flow cell without the need for chemical labels, and the entire binding event can be analyzed in real time (association and dissociation). This allows for the determination of both kinetic and thermodynamic parameters through various data analyses [101]. SPR assays can also be designed to measure binding to two targets simultaneously, and are also potential candidates for MoA-reflective potency by binding assays. The case studies presented below provide two examples of assay formats for the purpose of measuring concurrent antigen binding by SPR.

Drawbacks for both ELISA and SPR are that it can be difficult to measure the impact of either target density (avidity effects) on BsAb binding, which can be important factors for a BsAb's activity in an in-vivo context. SPR allows for control of target density by depositing different amounts of capture ligand on the sensor chip. Binding of the therapeutic antibody can then be characterized under the different conditions to investigate the effects of receptor density on binding affinity/avidity [102]. However, the fact that BsAbs bind two targets, with varying levels of avidity depending on structure/format, can make this type of experiment challenging to design and interpret using label-free mass-based detection by SPR [103]. Additionally, there are open questions with respect to the in-vivo relevance of binding events [e.g., how relevant is binding to an immobilized ligand on a chip, or is solution-based association of a truncated ligand (such as a peptide or extracellular domain)

reflective of binding to a cell surface receptor?] [104]. Investigators have used SPR to measure binding of aCD20 mAbs to membrane bound CD20, and developed sophisticated software that makes it possible to extract and analyze individual binding events from heterogeneous mixtures. There have also been reports of affixing multiple ligands on a sensor surface in a solution-like context using DNA-directed immobilization using SPR, which would be useful for characterizing BsAbs. New biosensor technologies that allow for discrete detection of both binding events and precise control over surface density, as well as advances in SPR data analysis and experimental design, may provide avenues for more thoroughly investigating complex binding events under increasingly biologically relevant conditions in the future [105–109].

based on both individual readouts: two binding events can be measured, and the third parameter can be accurately calculated based on these measurements.

#### Cell Surface Ligand Binding Assays

Binding properties of investigational BsAbs to their targets can also be assessed by flow cytometry, which can be used to measure binding specificity and selectivity of BsAbs in a cellular context—information that is not captured in a traditional SPR or ELISAbased binding assay. Flow cytometry, is a fluidics and optics-based method that evaluates fluorescently-labeled cell suspensions in a single cell flow to capture receptor- or antigenbinding events in intact cells. However, flow cytometric analysis of antibody binding is an indirect measurement of kinetic values and it should be used in combination with SPR analysis to provide truly comprehensive, label-free, and accurate kinetic data for the antibodies being studied.

In addition to flow-cytometry assays, cell-based reporter assays have been developed to measure gene expression in response to disruption of an inhibitory binding interaction, such as PD-L1/PD-1 [93]. As a result, these assays provide a functional measure of BsAb binding as opposed to, for example, directly measuring binding affinity by SPR. In the case studies discussed below, variations of flow cytometric analysis are used to demonstrate the preferential binding, receptor blocking, and avidity of binding to dual-antigen-expressing target cells. In addition, application of a reporter assay to assess BsAb-mediated blockade of receptor-ligand interaction between the antigen-expressing tumor cells and effector cells is reviewed.

uate the binding activities of the investigational BsAb. Wild-type ectopically hPD-L1 expressing CHO cells (CHO.PD-L1) were incubated with test antibodies, labeled with a fluorescent secondary antibody, and analyzed by flow cytometry. Dose-dependent binding specific to CHO.PD-L1 cells was observed for the BsAb. These binding activities were replicated in several representative cancer cells endogenously expressing both CSPG4 or PD-L1. In addition, a flow cytometry-based competitive binding assay was used to assess the overall binding strength (avidity) of PD-L1xCSPG4 BsAb to CSPG4+/PD-L1+ cancer cells. BsAb binding was strongly inhibited in the presence of competing parental anti-CSPG4 mAb and only weakly inhibited in the presence of competing PD-L1-blocking mAb. These experiments demonstrate that PD-L1xCSPG4 binds to both PD-L1 and CSPG4 and that the strength of the interaction between the BsAb and CSPG4+/PD-L1+ cancer cells is primarily dominated by binding to CSGA4. To further show that the enhanced binding of the BsAb to CSPG4+/PD-L1+ cells is driven by avidity, cells were pre-incubated with a fluorescent anti-PD-L1 mAb, before being exposed to the test BsAb and a control BsAb, capable of binding PD-L1 but not CSPG4. The EC50 of PD-L1xCSPG4 for displacing the probe was substantially lower compared to the control BsAb. Performing the experiment in the presence of an anti-GSPG4 mAb increased the EC50 of the PD-L1xCSPG4 BsAb to a level similar to the control BsAb. Together these flow cytometry-based binding assays demonstrated that the PDL1xCSPG4 BsAb has enhanced selectivity for CSPG4+/PD-L1+ cancer cells driven by avidity binding.

• Case Study: Cell-based reporter assay to measure cell surface binding of PDL1xCSPG4 BsAb [93]: The authors further evaluated the role of CSPG4 in mediating the PD-L1 blocking capacity of the PDL1xCSPG4 BsAb using a PD-1/PD-L1 blockade reporter bioassay. The assay relies on co-culturing of Jurkat.PD-1-NFAT-luc reporter T cells (Jurkat cells engineered to express luciferase under the control of a NFAT response element and PD-1) and CHO.PDL1/CD3 cells (CHO cells engineered to express PD-L1 and a membrane-linked agonistic anti-CD3 antibody). Upon successful interaction of PD-1 and PD-L1 between the two cell types, TCR signaling and downstream NFATmediated luciferase activity in the Jurkat cells is inhibited. In contrast, interrupting the PD-1/PD-L1 interaction leads to NFAT-mediated luciferase activity. Addition of the PDL1xCSPG4 BsAb to the co-culture disrupted the PD-1/PD-L1 interaction between the two cell types in a dose-dependent manner, as measured by luminescence detection. Next, they tested the role of CSPG4 mAb in PD-1/PD-L1 blocking capacity of PDL1xCSPG4 BsAb by replacing the CHO.PD-L1/CD3 cells with a CSPG4+/PD-L1+ cancer cell line (the CD3 stimulation of T cells was achieved by pre-treating the cells with BIS1; an EpCAM-directed CD3-agonistic bsAb). Stimulated reporter T cells were co-cultured with the double-positive cells in the presence of PDL1xCSPG4 BsAb or controls, with and without anti-CSPG4 mAb. The ability of the PDL1xCSPG4 BsAb to block PD-1/PD-L1 interaction was reduced in the presence of anti-CSPG4 mAb. These findings suggest that the BsAb's PD-1/PD-L1-disrupting activity will be enhanced against CSPG4+/PD-L1+ cells compared to CSPG4-/PD-L1+ cells.

#### *3.3. BsAb Bioassay: Potency Assays*

In particular, the strategy of using a potency assay for BsAbs is challenging due to its complicated MoA with two target bindings, and it should be tailored to be MoA-reflective while meeting QC and regulatory expectations to be robust and sensitive methods to detect any structural changes in stability. One interesting question with respect to the BsAb potency assay is if two assays are needed for each target binding or if one potency assay would suffice. Depending on its MoA, either one or two potency assays would be suitable, but it is preferred to have one potency assay to measure synergistic biological effects of two target bindings or a dual read-out of the binding assays in a single assay.

A single assay that can fully capture the bioactivity of the therapeutic molecule is advantageous from both a cost/labor perspective and from a control perspective—synergistic

effects resulting from dual antigen binding may be missed if data from multiple assays measuring discrete events are used. However, in order to show the assay is suitably MoA-reflective, the key events in the MoA must be relatively well understood, and characterization assays designed to measure each event (e.g., binding to either antigen, receptor activation, etc.) are needed. The two case studies below describe the development and justification of single QC potency assays to measure changes in bioactivity for (1) a TDB and (2) a DAF that inhibits ligand binding to two distinct cell surface receptors.

#### *3.4. BsAb Bioassay: Effector Function Assays*

Some BsAbs target cell surface proteins or receptors with the intent of enhancing effector function. One arm often targets a tumor-associated antigen while the other targets an immune system-evading surface protein (such as CD47 or CD55/59), increasing susceptibility of the tumor cell to lysis by complement or NK cells, or phagocytosis by macrophages.

Other BsAbs have a primary MoA that does not involve effector function (e.g., TDB, or receptor blocker) but have an effector-competent Fc domain and can also exert cell killing activity through effector function. Depending on the MoA and other molecule-specific factors, effector function can be associated with unfavorable safety events, and so, effectorsilenced Fc domains are preferred [110,111]. In other cases effector function enhances a molecule's activity [54,57].

#### *3.5. BsAb Bioassay: Impurities Assays*

Impurities assays for BsAbs are often physicochemical assays such as size-exclusion chromatography (to measure aggregates and fragments), imaging capillary isoelectric focusing/ion exchange chromatography (to measure charge variants), and mass spectrometry (to sensitively identify and/or quantify post-translational modifications and other trace variants) [112], which are commonly used to characterize impurities for conventional mAbs. However, the unique structure of BsAbs can produce unique product variants with impacts to safety and/or bioactivity that are not fully addressed by physicochemical assays. The nature/activity of such impurities is rooted in the structure of the molecule, its production

process, and MoA. In order to illustrate this point a case study describing the development of a bioassay to measure T-cell activating impurities for a TDB is described below.

• Case Study: Luciferase reporter T cell activation assay to measure functional effects of impurities on CD3e-targeting TDB [95]: A CD3e-targeting TDB produced by knobsinto-holes technology and assembled in vitro contains a number of product-related impurities with the potential to activate T-cells in the absence of target cells. For example, aggregates and aCD3 homodimer, which result from the mispairing of aCD3 half antibody fragments during production, are characterized by multivalent binding to CD3 and can crosslink the TCR resulting in activation. These impurities are a safety concern because T-cell activation is linked to adverse events such as cytokine release syndrome. While aggregates and aCD3 HD can be measured using analytical methods, a bioassay is needed to assess their biological impact, such as target-independent T-cell activation. To address this need, the authors developed a reporter gene assay that measures T-cell activation in the absence of target cells using Jurkat T-cells engineered to express luciferase when activated. T-cell activation of product-related impurities present in the TDB formulation was quantified relative to T-cell activation by aCD3 HD standard. Using this assay, the authors were able to characterize the T-cell activating activities of aggregates and other product-related impurities, in order to get an idea of their potential impacts to safety and inform on the overall control strategy. Additionally, because the assay is a "catchall" assay that measures the combined T-cell activating activity of product-related impurities that may be present in a given sample, the method is able to provide reassurance that combinations of impurities are not leading to unexpected T-cell activation. Such combination effects would not be identified using physicochemical methods alone.


**4.4 Possibility of drug design using topological data analysis**

If we have a dataset containing information about compounds with respect to their structural features, toxicity, binding affinity to the target then we can use TDA, a mathematical technique to create a similarity network of the compounds by studying shapes preserving high-dimensionality. TDA will enable us to visualize our compound library as a two-dimensional network, with compounds (located in nodes) linked by a series of edges indicating their degree of mutual similarity. As a result, two compounds with identical properties will appear closer together in the network, whereas two compounds with vastly different properties will appear farther apart. This network would make it simple to create subgroups or families of related compounds, which could then be used to choose the best compound.

#### **Table 2.**

*List of AI-Based Computational Tools for Drug Discovery.*

#### **4.5 Possibility drug design using Quantum machine learning**

The Quantum Computer Algorithm (QC) was introduced as a way to speed up classical machine learning algorithm. However, modern computers are not enough to analyze the behavior of the atoms in a molecule. Even the most powerful supercomputers at this time can only simulate relatively simple molecules by significantly limiting their ability to predict the interaction of complex molecules and atoms. Classical computing (CC) and big data analysis methods can screen desired properties of molecules. Researchers use Molecular simulator to simulate interactions between electrons of each atom to test how they react with each other in the real world. However, due to CC's relatively limited processing capacity, the computationally designed drug fails to deliver the desired results in 90 percent cases during the first phase of the clinical trial causing loss of billions of dollars every year. When Google announced a successful quantum computing experiment (QC) that has achieved what is called "quantum supremacy" (calculations that are too complex to do using CC), it was praised by many peoplearound the world as a key moment for QC.

*Drug Design for Malaria with Artificial Intelligence (AI) DOI: http://dx.doi.org/10.5772/intechopen.98695*

It is also an important development for drug discovery. Indeed, QC can change the drug discovery game entirely by packing enough computational muscles to enable molecular analysis at an unprecedented scale which was completely unimaginable with a CC. Additionally, quantum machine learning (QML) which uses quantum algorithms to perform complex algorithms of learning assignments [72] can augment the computational tools of drug discovery programs even further. Classical machine learning has already shown a significant promise in drug discovery. QML allows scientists to translate classical ML algorithms into quantum circuits to run an ultra-strong quantum computer efficiently. This quantum computer will become more efficient in future as the quantum technologies become less prone to mistakes. Scientists from the University of Warwick, the University of Luxembourg, and the University of Berlin recently created a deep ML algorithm that could predict the molecule's quantum state faster than before. "Solve the fundamental equation of quantum mechanics in conventional ways requires high-performance computing resources and computational months," explained the laboratory news. The team said that "the new AI algorithm developed can provide accurate predictions in seconds on a laptop or cellphone." Researchers from Pfizer have made similar progress, using modeling techniques called predictions of the crystal structure (CSP) to map molecular 3D structures - calculations that usually take months to solve. However, there is a long path to travel before we can say that we have achieved a practical quantum advantage. However, QC and QML hold extraordinary promises for the pharmaceutical business - which, when refined, will pave the way towards the development of new drugs as well as safer and cheaper health products for patients in the future.